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Cover for The Great Mental Models, Volume 1: General Thinking Concepts, Author, Shane Parrish and Rhiannon Beaubien
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Book Title, The Great Mental Models, Volume 1: General Thinking Concepts, Author, Shane Parrish and Rhiannon Beaubien, Imprint, Portfolio
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Contents

内容

Preface

前言

Introduction: Acquiring Wisdom

引言:获得智慧

The Map Is Not the Territory

地图并非疆域本身

Circle of Competence

能力圈

Supporting Idea: Falsifiability

支持观点:可证伪性

First Principles Thinking

第一性原理思维

Thought Experiment

思想实验

Supporting Idea: Necessity and Sufficiency

支持观点:必要性和充分性

Second-Order Thinking

二阶思维

Probabilistic Thinking

概率思维

Supporting Idea: Causation vs. Correlation

支持观点:因果关系与相关性。

Inversion

倒置

Occam’s Razor

奥卡姆剃刀

Hanlon’s Razor

汉隆剃刀

Afterthoughts and Acknowledgments

后记与致谢

Notes

笔记

About the Author

作者简介

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The key to better understanding the world is to build a latticework of mental models.

理解世界的关键在于构建心智模型网络。

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Preface

前言

Education doesn’t prepare you for the real world. At least, it didn’t prepare me. I was two weeks into my job at an intelligence agency on September 11, 2001, when the world suddenly changed. The job I had been hired to do was no longer the one that was needed. Instead, I was thrust into a series of promotions for which I had received no guidance and that came with responsibilities I had no idea how to navigate. I had a computer science degree; I came from a world of 1s and 0s, not people, families, and interpersonal dynamics. Now, I found that my decisions affected not only my employees but their families; not only my country but other countries. The problem? I had no idea how to make decisions. I only knew I had an obligation to make the best decisions I could.

教育并不能让你为现实世界做好准备。至少,它没能让我做好准备。2001年9月11日,我入职情报机构两周后,世界骤然改变。我原本的工作岗位不再需要了。取而代之的是,我被推上了一系列晋升岗位,却没有任何人指导我,随之而来的是一系列我完全不知如何应对的责任。我拥有计算机科学学位;我来自一个由0和1构成的世界,而不是一个充满人、家庭和人际关系的世界。现在,我发现我的决定不仅影响我的员工,还影响他们的家人;不仅影响我的国家,还影响其他国家。问题是?我不知道该如何做决定。我只知道我有义务尽我所能做出最好的决定。

To improve my ability to make decisions, I looked around and found some mentors. I watched them carefully and learned from them. I read everything I could about making decisions. I even took some time to go back to school and earn my MBA, hoping that I would finally learn how to make better decisions, as if “making better decisions” was some end state rather than a constantly evolving journey.

为了提升决策能力,我四处寻找导师,认真观察他们的工作,并向他们学习。我阅读了所有能找到的关于决策的书籍。我甚至还抽出时间重返校园攻读MBA,希望最终能学会如何做出更好的决策,仿佛“做出更好的决策”是一个最终目标,而不是一个不断进步的过程。

My belief that the MBA program was a good use of my time eroded quickly. When I showed up to write an exam, only to find out it was an open-book test, I realized my expectations were entirely wrong and in need of updating. Was I in a master’s program or grade school? Some days, I couldn’t tell. And yet that program is where everything changed for me.

我最初认为攻读MBA课程是物有所值的想法很快就动摇了。当我参加考试时,却发现竟然是开卷考试,我意识到自己的预期完全错误,需要彻底修正。我到底是在读硕士还是在上小学?有时候,我甚至分不清。然而,正是这个项目彻底改变了我的人生。

I realized that I couldn’t fail, as long as I knew where the answers were in the books I could bring to the exams. This was quite liberating. I stopped putting effort into my assignments and started learning about someone who was often casually mentioned in class. That person was Charlie Munger. I went from studying theoretical examples that were completely divorced from the real world to studying the wisdom behind the achievements of one of the most successful businessmen of all time. Munger, who you will come to know in these volumes, is the deceased billionaire business partner of Warren Buffett at Berkshire Hathaway. He was easy to like: intelligent, witty, and irreverent. Finding Munger opened the door to unexpected intellectual pleasure. I felt I had finally found knowledge that was useful, because it was gained from someone’s real effort to better understand how the world works. It was so much more satisfying to learn from someone who had tried to put many theories into practice and was willing to share his results than from anemic economic theorists. The fact that Munger was so professionally successful made it even more compelling.

我意识到,只要我知道答案在考试要带的书里,我就不会失败。这让我如释重负。我不再费力做作业,而是开始研究课堂上经常被随意提及的一个人——查理·芒格。我从研究那些完全脱离现实世界的理论案例,转而研究这位史上最成功的商人之一的成就背后的智慧。芒格,你会在接下来的书中了解到他,他是已故的亿万富翁,曾是沃伦·巴菲特在伯克希尔·哈撒韦公司的商业伙伴。他很容易让人喜欢:聪明、风趣、不拘一格。发现芒格为我打开了一扇通往意想不到的知识宝库的大门。我感觉自己终于找到了真正有用的知识,因为它源于某人为更好地理解世界运行规律而付出的真正努力。向一位尝试将众多理论付诸实践并愿意分享成果的人学习,远比向那些苍白无力的经济理论家学习要令人满足得多。芒格在事业上取得的巨大成功,更使这本书更具说服力。

Munger had a way of thinking through problems using what he calls a broad latticework of mental models. These are chunks of knowledge from different disciplines that can be simplified and applied to better understand the world. The way Munger described it, these mental models help identify what information is relevant in any given situation and the most reasonable parameters to work within. His track record in business shows that this doesn’t just make sense in theory but is devastatingly useful in practice.

芒格运用他所谓的“思维模型网络”来思考问题。这些思维模型融合了不同学科的知识,可以进行简化并应用于更好地理解世界。正如芒格所描述的,这些思维模型有助于识别特定情况下哪些信息是相关的,以及最合理的运作参数。他在商业上的成功证明,这不仅在理论上说得通,而且在实践中也极具价值。

I started writing about my learnings, the result being my website, Farnam Street ( https://fs.blog ). The past eight years of my life have been devoted to identifying and learning the mental models that have the greatest positive impact, and trying to understand how we think, how we update, how we learn, and how we can make better decisions.

我开始记录我的学习心得,最终创建了我的网站 Farnam Street (https://fs.blog)。过去八年,我一直致力于识别和学习那些具有最大积极影响的思维模式,并努力理解我们如何思考、如何更新知识、如何学习以及如何做出更好的决策。

I joke with my kids that if you want to suck up someone’s brain, you should simply read a book. All the great wisdom of humanity is written down somewhere. One day, when we were talking about mental models, the kids asked if we had the mental models book. This made me pause. I was struck with the realization that such a book didn’t exist. I didn’t have something I could share with my kids, and that was a problem—a solvable problem.

我经常跟孩子们开玩笑说,想了解别人的智慧,读读书就行了。人类所有的伟大智慧都记录在某处。有一天,我们聊到心智模型的时候,孩子们问我们有没有一本关于心智模型的书。这让我愣住了。我突然意识到,竟然没有这样一本书。我没有可以和孩子们分享的东西,这真是个问题——一个可以解决的问题。

This book, and the three further volumes that follow, are the books I wish had existed years ago, when I started learning about mental models. They are my homage to the idea that we can benefit from understanding how the world works and apply that understanding to keep us out of trouble.

这本书以及接下来的三卷,正是我多年前开始学习心智模型时梦寐以求的书籍。它们是我对“理解世界运行的规律,并运用这种理解来避免麻烦”这一理念的致敬。

The ideas in these volumes are not my own, nor do I deserve any credit for them. They come from the likes of Charlie Munger, Nassim Nicholas Taleb, Charles Darwin, Peter D. Kaufman, Peter Bevelin, Richard Feynman, Albert Einstein, and so many others. As the Roman poet Terence wrote: “Nothing has yet been said that’s not been said before.” We’ve only curated, edited, and shaped the work of others before me.

这些著作中的观点并非我原创,我也不应为此获得任何赞誉。它们源自查理·芒格、纳西姆·尼古拉斯·塔勒布、查尔斯·达尔文、彼得·D·考夫曼、彼得·贝弗林、理查德·费曼、阿尔伯特·爱因斯坦等众多先贤。正如罗马诗人泰伦斯所言:“凡是前人未曾说过的话,如今也无从谈起。”我们只是对前人的研究成果进行了整理、编辑和完善。

The timeless, broad ideas in these volumes are for my children, and their children, and their children’s children. In creating these books, I hope to enable others to approach problems with clarity and confidence, helping to make their journey through life more successful and rewarding.

这些书中蕴含的永恒而深远的理念,是为我的孩子、他们的孩子以及他们子孙后代而写的。我希望通过创作这些书籍,能够帮助人们以清晰而自信的视角看待问题,从而使他们的人生旅程更加成功、更加充实。

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Introduction: Acquiring Wisdom

引言:获得智慧

You’re only as good as your tools.

你的实力取决于你的工具。

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It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent.

—Charlie Munger

令人惊讶的是,像我们这样的人,与其一味追求聪明,不如努力做到始终不愚蠢,这样反而获得了长远的优势。——查理·芒格
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In life and business, the person with the fewest blind spots wins. Blind spots are the source of all poor decisions. Think about it: If you had perfect information, you would always make the best decision. In a poker game where you could see everyone’s cards, you’d play your hand perfectly. You wouldn’t make any mistakes.

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在生活和商业中,盲点最少的人才能最终获胜。盲点是所有糟糕决策的根源。想想看:如果你掌握了所有信息,你总能做出最佳决策。在扑克游戏中,如果你能看到所有人的底牌,你就能完美地打出自己的牌,不会犯任何错误。

Unfortunately, we have a lot of blind spots. And while we can’t eliminate them, we can reduce them. Reducing blind spots means we see, interact with, and move closer to understanding reality. We think better. And thinking better is about finding simple processes that help us work through problems from multiple dimensions and perspectives, allowing us to better choose solutions that fit the objective. The skill behind finding the right solutions for the right problems is one form of wisdom.

遗憾的是,我们存在许多盲点。虽然我们无法完全消除它们,但我们可以减少它们。减少盲点意味着我们能够更好地观察、互动并理解现实。我们的思维会更加敏锐。而更敏锐的思维则在于找到一些简单的方法,帮助我们从多个维度和角度解决问题,从而更好地选择符合目标的解决方案。找到针对正确问题的正确解决方案,正是智慧的一种体现。

This book is about the pursuit of that type of wisdom—the pursuit of uncovering how things work, the pursuit of going to bed smarter than when we woke up. It is a book about getting out of our own way so we can better understand how the world really is. Decisions based on improved understanding will be better than ones based on ignorance. While, inevitably, we can’t predict which problems will crop up in life, we can learn time-tested ideas that help position us for whatever the world throws at us.

这本书讲述的是如何追求那种智慧——探索事物运行的规律,追求每天醒来时比醒来时更睿智。它教我们如何克服自身的局限,从而更好地理解世界的真实面貌。基于更深刻理解的决策,远胜于基于无知的决策。虽然我们无法预知生活中会遇到哪些问题,但我们可以学习一些经受时间考验的理念,帮助我们更好地应对人生中的各种挑战。

Perhaps more importantly, this book is about avoiding problems. This often comes down to understanding a problem accurately and seeing the secondary and subsequent consequences of any proposed action. The author and explorer of mental models Peter Bevelin put it best: “I don’t want to be a great problem solver. I want to avoid problems—prevent them from happening and do it right from the beginning.” [1]

或许更重要的是,这本书讲述的是如何避免问题。这通常归结为准确理解问题,并预见任何拟议行动的次要后果和后续影响。心智模型的作者和探索者彼得·贝弗林对此做了最好的诠释:“我不想成为一个伟大的问题解决者。我想避免问题——防止问题发生,并且从一开始就做对。”[1]

How can we do things right from the beginning?

我们如何才能从一开始就把事情做好?

We must understand how the world works and adjust our behavior accordingly. Contrary to what we’re led to believe, thinking better isn’t about being a genius. It is about the processes we use to uncover reality and the choices we make once we do.

我们必须了解世界的运行规律,并据此调整自身的行为。与我们通常被灌输的观念相反,更优秀的思考能力并非意味着成为天才,而是关乎我们揭示现实的方法以及揭示现实后所做的选择。

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How This Book Can Help You

这本书能如何帮助你

This is the first of four volumes aimed at defining and exploring the Great Mental Models—those with the broadest utility across our lives.

这是旨在定义和探索伟大思维模型(即在我们生活中具有最广泛用途的思维模型)的四卷本中的第一卷。

Mental models describe the way the world works. They shape how we think, how we understand, and how we form beliefs. Largely subconscious, mental models operate below the surface. We’re not generally aware of them, and yet when we look at a problem, they’re the reason we consider some factors relevant and others irrelevant. They are how we infer causality, match patterns, and draw analogies. They are how we think and reason.

心智模型描述了世界的运作方式。它们塑造了我们的思维方式、理解方式和信念形成方式。心智模型大多潜藏于潜意识中,在我们意识层面之外运作。我们通常意识不到它们的存在,然而,当我们审视一个问题时,正是它们决定了我们认为某些因素相关而另一些因素无关紧要。它们帮助我们推断因果关系、匹配模式和进行类比。它们构成了我们的思考和推理方式。

A mental model is a compression of how something works. Any idea, belief, or concept can be distilled down. Like maps, mental models reveal key information while ignoring the nonessential. For example, you likely have a useful idea about how inertia works, even though you don’t know all the technical details.

心智模型是对事物运作方式的精简概括。任何想法、信念或概念都可以被提炼出来。就像地图一样,心智模型揭示关键信息,同时忽略无关信息。例如,即使你不了解所有技术细节,你也可能对惯性如何运作有一个有用的概念。

Mental models help us better understand the world. While this might sound a bit academic, it’s not. For example, velocity helps us understand that both speed and direction matter. Reciprocity helps us understand how going positive and going first gets the world to do most of the work for us. The idea of a margin of safety helps us understand that things don’t always go as planned. Relativity shows us how a different perspective changes everything. The list goes on.

心智模型帮助我们更好地理解世界。这听起来或许有些学术化,但并非如此。例如,速度模型帮助我们理解速度和方向都至关重要。互惠原理帮助我们理解,积极主动、抢占先机如何让世界为我们完成大部分工作。安全边际的概念帮助我们理解,事情并非总能按计划进行。相对论则向我们展示了不同的视角如何改变一切。这样的例子不胜枚举。

It doesn’t matter what the model is or where it comes from—the question to ask yourself is whether it is useful. The world is not divided into distinct disciplines. For example, business professors won’t discuss physics in their lectures, but they should. Velocity teaches us that going in the right direction matters more than how fast you go. Kinetic energy teaches us that your company’s velocity matters more than its size when creating an impact in the market. Understanding and applying these insights helps you outperform your competition.

模型是什么,源自何处,都无关紧要——关键在于它是否实用。世界并非泾渭分明地划分成各个学科。例如,商学院教授不会在课堂上讨论物理学,但他们应该这样做。速度告诉我们,方向正确比速度快更重要。动能告诉我们,在市场中产生影响时,公司的发展速度比规模更大。理解并运用这些洞见,能助你超越竞争对手。

While it helps to think of each model as a map, collectively they act as lenses through which you can see the world. Each lens (model) offers a different perspective, revealing new information. Looking through one lens lets you see one thing, and looking through another reveals something different. Looking through them both reveals more than looking through each one individually.

虽然将每个模型想象成一张地图会有所帮助,但它们共同构成了观察世界的透镜。每个透镜(模型)提供不同的视角,揭示新的信息。透过一个透镜观察一件事,透过另一个透镜观察则揭示另一件事。同时透过两个透镜观察,比单独透过每个透镜观察能获得更多信息。

Whether we realize it or not, mental models help us think at the subconscious level. They shape what we see, what we choose to ignore, and what we miss entirely. While there are millions of mental models, these volumes focus on the ones with the greatest utility—the all-star team of mental models.

无论我们是否意识到,心智模型都在潜意识层面帮助我们思考。它们塑造着我们所看到的、我们选择忽略的以及我们完全错过的事物。虽然心智模型数以百万计,但本书重点介绍其中最具实用性的——心智模型中的佼佼者。

Volume 1 presents the first nine models, which are general thinking concepts. Although these models are hiding in plain sight, they are useful tools that you likely were never directly taught. Put to proper use, they will improve your understanding of the world we live in and your ability to look at a situation through different lenses, each of which reveals a different layer. They can be used in a wide variety of situations and are essential to making rational decisions, even when there is no clear path. Collectively, they will allow you to walk around any problem in a three-dimensional way.

第一卷介绍了前九个模型,这些都是通用的思维概念。虽然这些模型看似显而易见,但它们却是你可能从未被直接教授过的实用工具。正确运用它们,将提升你对所处世界的理解,并增强你从不同视角看待问题的能力,每个视角都能揭示问题的不同层面。它们适用于各种情况,即使在没有明确方向的情况下,对于做出理性决策也至关重要。总而言之,它们将帮助你以三维视角审视任何问题。

Our approach to the Great Mental Models rests on the idea that the fundamentals of knowledge are available to everyone. There is no discipline that is off-limits—the core ideas from all fields of study contain principles that reveal how the universe works and are therefore essential to navigating it. Our models come from fundamental disciplines that most of us have never studied, but no prior knowledge is required, only a sharp mind with a desire to learn.

我们构建“伟大思维模型”的方法基于这样一个理念:知识的基础知识是人人皆可获得的。没有任何学科是禁忌——所有学科的核心思想都蕴含着揭示宇宙运行规律的原则,因此对于我们理解和驾驭宇宙至关重要。我们的模型源自大多数人从未接触过的基础学科,但无需任何先验知识,只需一颗思维敏捷、求知欲强的心。

Why Mental Models?

为什么需要心智模型?

There is no system that can prepare us for all risks. Factors of chance introduce a level of complexity to any situation that is not entirely predictable. But being able to draw on a repertoire of timeless mental models can help us minimize risk by better understanding the forces that are at play. Likely consequences don’t have to be a mystery.

没有任何系统能够让我们做好应对所有风险的准备。偶然因素会给任何情况带来复杂性,使其无法完全预测。但是,运用一系列经久不衰的思维模式可以帮助我们更好地理解各种影响因素,从而最大限度地降低风险。可能的后果不必再是个谜。

Not having the ability to shift perspective by applying knowledge from multiple disciplines makes us vulnerable. Mistakes can become catastrophes whose effects keep compounding, creating stress and limiting our choices. Multidisciplinary thinking—learning these mental models and applying them across our lives—creates less stress and more freedom. The more we can draw on the diverse knowledge contained in these models, the more solutions will present themselves.

缺乏运用多学科知识转换视角的能力会让我们变得脆弱。错误可能演变成灾难,其影响不断累积,造成压力并限制我们的选择。跨学科思维——学习这些思维模式并将其应用于我们的生活中——可以减轻压力,带来更多自由。我们越能利用这些模式中蕴含的多元知识,就越能找到解决方案。

Understanding Reality

理解现实

“Understanding reality” is a vague phrase, one you’ve already encountered a few times as you’ve read this book. Of course, we want to understand reality, but how do we do that? And why is it important?

“理解现实”是一个含义模糊的短语,你在阅读本书的过程中已经多次遇到它。当然,我们都想理解现实,但我们该如何理解呢?为什么理解现实如此重要?

In order to see a problem for what it is, we must first break it down into its substantive parts, so the interconnections can reveal themselves. This bottom-up perspective allows us to expose what we believe to be the causal relationships within the problem and determine how they will govern the situation both now and in the future. Being able to accurately describe the full scope of a situation is the first step to understanding it.

为了看清问题的本质,我们首先必须将其分解成各个组成部分,这样才能揭示它们之间的相互联系。这种自下而上的视角使我们能够揭示问题内部的因果关系,并确定它们将如何影响当前和未来的局势。能够准确描述局势的全貌是理解局势的第一步。

Using the lenses of our mental models helps us illuminate these interconnections. The more lenses used on a given problem, the more reality reveals itself. The more of reality we see, the fewer blind spots we have. The fewer blind spots we have, the better the options at our disposal.

运用我们既有的思维模式有助于我们理解这些相互关联。看待某个问题时使用的视角越多,就越能看清真相。我们看到的真相越多,盲点就越少。盲点越少,我们可选择的方案就越多。

Simple and well-defined problems won’t need many lenses, as the variables that matter are known; so too are the interactions between them. In such cases, we generally know what to do to get the intended result with the fewest side effects possible. When problems are more complicated, however, the value of having a brain full of lenses becomes readily apparent.

简单且定义明确的问题不需要太多视角,因为关键变量及其相互作用都已明确。在这种情况下,我们通常知道如何以尽可能少的副作用获得预期结果。然而,当问题变得更加复杂时,拥有丰富的视角就显得尤为重要。

That’s not to say all lenses (or models) apply to all problems. They don’t. And it’s not to say that having more lenses (or models) will be an advantage in thinking through all problems; it won’t. This is why learning and applying the Great Mental Models is a process that takes some work. But the truth is, most problems are multidimensional, and thus having more lenses often offers significant help with the problems we are facing.

这并不是说所有视角(或模型)都适用于所有问题。事实并非如此。这也不是说拥有更多视角(或模型)就能帮助我们思考所有问题;事实并非如此。正因如此,学习和应用伟大的思维模型需要付出一定的努力。但事实是,大多数问题都是多维度的,因此拥有更多视角往往能极大地帮助我们应对当前面临的问题。

Keeping Your Feet on the Ground

脚踏实地

In Greek mythology, Antaeus was the human-giant son of Poseidon, god of the sea, and Gaia, Mother Earth. Antaeus had a strange habit: he would challenge all those who passed through his country to a wrestling match. As in wrestling today, the goal was to force the opponent to the ground. Antaeus always won, and his defeated opponents’ skulls were used to build a temple to his father. While Antaeus was undefeated and nearly undefeatable, there was a catch to his invulnerability. His epic strength depended on constant contact with the earth; when he lost touch with the earth, he lost all his strength. The great hero lost to Heracles, who simply lifted him off the ground.

在希腊神话中,安泰俄斯是海神波塞冬和大地之母盖亚的儿子,一个半人半巨人。安泰俄斯有个怪癖:他会向所有路过他领地的人挑战摔跤。就像今天的摔跤一样,目标是将对手摔倒在地。安泰俄斯总是获胜,他用战败对手的头骨建造了一座供奉他父亲的神庙。虽然安泰俄斯战无不胜,几乎无人能敌,但他的无敌之身却并非无懈可击。他强大的力量源于与大地的持续接触;一旦失去与大地的接触,他就会失去所有的力量。这位伟大的英雄最终败给了赫拉克勒斯,赫拉克勒斯轻而易举地将他举离了地面。

On the way to the Garden of the Hesperides, Heracles was to fight Antaeus as one of his twelve labors. After a few rounds in which Heracles flung the giant to the ground, only to watch him revive, he realized he could not win by using traditional wrestling techniques. Instead, Heracles fought to lift Antaeus off the ground. With the earthly connection broken, Antaeus was separated from the source of his power, causing him to lose his strength. From that point on, it was easy for Heracles to crush him. [2] , [3]

在前往赫斯珀里得斯花园的途中,赫拉克勒斯要与安泰俄斯搏斗,这是他十二项功绩之一。几回合过后,赫拉克勒斯将巨人摔倒在地,却眼睁睁看着他复活,他意识到自己无法用传统的摔跤技巧取胜。于是,赫拉克勒斯转而尝试将安泰俄斯举离地面。由于与大地的联系被切断,安泰俄斯失去了力量的源泉,力量也随之消散。从那时起,赫拉克勒斯便轻而易举地击败了他。[2] , [3]

When understanding is separated from reality, we lose our powers to make better decisions. Understanding must constantly be tested against reality and updated accordingly. This isn’t a box we can tick, a task with a definite beginning and end, but rather a continuous process.

当理解脱离现实时,我们便会丧失做出更明智决策的能力。理解必须不断地接受现实的检验,并据此更新。这并非一个可以勾选的选项,也不是一个有明确开始和结束的任务,而是一个持续不断的过程。

We all know the person who seems to have all the answers. They know how to fix all the problems at work, solve world hunger, and get in shape (if only they wanted to). If you don’t test your ideas against the real world—if you don’t keep contact with the earth— how can you be sure you understand it? While pontificating with friends over a bottle of wine at dinner can be fun, the only way you’ll know the extent to which you understand reality is to put your ideas into action.

我们都认识那种似乎无所不知的人。他们知道如何解决工作中的所有问题,消除世界饥饿,还能保持身材(如果他们愿意的话)。如果你不将你的想法与现实世界进行检验——如果你不与现实世界保持联系——你又怎能确定自己真正理解它呢?虽然和朋友们在晚餐时一边品酒一边高谈阔论可能很有趣,但只有将你的想法付诸实践,你才能真正了解自己对现实的理解程度。

Getting in Our Own Way

阻碍我们前进

The biggest barrier to learning from the world is ourselves. It’s hard to understand a system that we are part of because we have blind spots, where we can’t see what we aren’t looking for and don’t notice what we don’t notice.

我们学习世界的最大障碍是我们自己。我们很难理解我们身处的系统,因为我们存在盲点,我们看不到我们不想看的东西,也注意不到我们没注意到的东西。

There are these two young fish swimming along, and they happen to meet an older fish, swimming the other way, who nods at them and says, “Morning, boys. How’s the water?” And the two young fish swim on for a bit, and then eventually one of them looks over at the other and goes, “What the hell is water?”

—David Foster Wallace [4]

有两条小鱼在水里游,碰巧遇到一条迎面游来的老鱼,老鱼朝它们点点头说:“早上好,孩子们。水怎么样?”两条小鱼继续游了一会儿,最后其中一条看着另一条说:“水到底是什么?”——大卫·福斯特·华莱士[4]

Our failures to update our mental models as we interact with the world spring primarily from three factors: not having the right perspective or vantage point, ego-induced denial, and distance from the consequences of our decisions. As we will learn in greater detail throughout these volumes on mental models, all of these can get in the way. They make it easier to keep our existing and flawed beliefs than to update them accordingly. Let’s briefly flesh out these flaws:

我们在与世界互动时未能更新心智模型,主要源于三个因素:缺乏正确的视角或立场、自我意识导致的否认,以及与自身决策后果的疏离。正如我们将在本系列关于心智模型的章节中详细探讨的那样,所有这些因素都会阻碍我们更新心智模型。它们使我们更容易固守现有的、有缺陷的信念,而不是根据实际情况进行相应的更新。让我们简要地阐述一下这些缺陷:

The first flaw is failure of perspective. We have a hard time seeing any system that we are a part of. We think our angle of perception is the right one and the only one.

第一个缺陷是视角错误。我们很难看清自己身处其中的任何系统。我们总认为自己的视角才是正确的,也是唯一正确的。

Galileo had a great analogy to describe the limits of our default perspective: Imagine you are on a ship that has reached constant velocity (meaning there is no change in speed or direction). You are belowdecks, and there are no portholes. You drop a ball from your raised hand to the floor. To you, it looks as if the ball is dropping straight down, thereby confirming gravity is at work.

伽利略曾用一个绝妙的比喻来描述我们默认视角的局限性:想象一下,你身处一艘匀速航行的船上(意味着速度和方向都没有变化)。你位于甲板下,没有舷窗。你举起一只手,将一个球扔到地板上。在你看来,球似乎是垂直下落的,从而证实了重力的作用。

Now imagine you are a fish (with special X-ray vision) and you are watching this ship go past. You see the scientist inside, dropping a ball. You register the vertical change in the position of the ball. But you are also able to see a horizontal change. As the ball was pulled down by gravity, it also shifted its position eastward by about twenty feet. The ship moved through the water, and therefore so did the ball. The scientist onboard, with no external point of reference, was not able to perceive this horizontal shift.

现在想象一下你是一条鱼(拥有特殊的透视能力),你正在观察一艘船驶过。你看到船上的科学家正在扔下一个球。你注意到球的位置发生了垂直变化。但你也能看到水平方向的变化。由于重力的作用,球在水中向下移动的同时,也向东移动了大约20英尺。船在水中移动,因此球也随之移动。船上的科学家由于没有外部参照物,无法感知到这种水平方向的变化。

This analogy shows us the limits of our perception. If we truly want to understand the results of our actions, we must be open to other perspectives. Allowing for other perspectives is also key to having productive relationships with others.

这个比喻揭示了我们感知的局限性。如果我们真的想了解自身行为的后果,就必须对其他观点持开放态度。接纳不同的观点也是与他人建立良好关系的关键。

The second flaw is ego—the part of us that’s afraid and always in competition. The ego is easily triggered and never feels satiated. Many of us tend to have too much invested in our opinion of ourselves to see the world’s feedback—the feedback we need to update our beliefs about reality. This creates a profound ignorance that keeps us repeatedly banging our heads against the wall. Our inability to learn from the world because of our ego arises for many reasons, but two are worth mentioning here. First, we’re often so afraid of what others will say about us that we fail to put our ideas out there and subject them to criticism; this way, we can always be right. Second, if we do put our ideas out there, and they’re criticized, our ego steps in to protect us—we become invested in defending, instead of upgrading, our ideas. This is antithetical to growth.

第二个缺陷是自我——我们内心那个充满恐惧且永远处于竞争状态的部分。自我很容易被激怒,而且永远不会感到满足。我们中的许多人往往过于执着于自我评价,以至于看不到外界的反馈——而这些反馈恰恰是我们需要用来更新对现实认知的。这造成了一种深刻的无知,让我们不断地碰壁。我们因为自我而无法从世界中学习的原因有很多,但其中有两个值得一提。首先,我们常常害怕别人对我们的评价,以至于不敢表达自己的想法,接受批评;这样一来,我们就能永远保持正确。其次,即使我们表达了自己的想法,一旦遭到批评,自我就会介入保护我们——我们会投入精力去捍卫自己的想法,而不是去改进它们。这与成长背道而驰。

The third flaw is distance. The further we are from the results of our decisions, the easier it is to maintain our current views rather than update them. When you put your hand on a hot stove, you quickly learn the natural consequence of doing so. You pay the price for your mistake. Since you are a pain-avoiding creature, you instantly update your knowledge. Before you touch another stove, you check to see if it’s hot. But you don’t just learn a micro lesson that applies in one situation. Instead, you draw a generalization, one that tells you to check before touching anything that could potentially be hot.

第三个缺陷是距离。我们离决策结果越远,就越容易固守现有观点,而不是更新它们。当你把手放在滚烫的炉子上时,你会很快明白这样做的后果。你会为自己的错误付出代价。由于人类天生厌恶痛苦,你会立即更新你的认知。在触摸另一个炉子之前,你会先检查它是否烫手。但你学到的不仅仅是适用于单一情境的微小教训。相反,你会从中总结出一个普遍规律,告诉你触摸任何可能烫手的东西之前都要先检查一下。

Large organizations often remove us from the direct consequences of our decisions. When we make decisions that other people carry out, we are one or more levels removed from their consequences and may not immediately be able to update our understanding—we come a little off the ground, if you will. The further we are from the feedback on our decisions, the easier it is to convince ourselves that we are right and avoid the challenge, the pain, of updating our views.

大型组织常常让我们远离决策的直接后果。当我们做出由他人执行的决策时,我们与决策的后果之间隔着一层或多层,可能无法立即更新我们的理解——可以说,我们离实际情况有点远。我们离决策反馈越远,就越容易说服自己是对的,从而逃避更新观点所带来的挑战和痛苦。

Admitting we’re wrong is tough. At a high level, it’s easier to fool ourselves that we’re right than it is at the micro level, because at the micro level we see and feel the immediate consequences. At a high or macro level, we are removed from the immediacy of the situation, and our ego steps in to create a narrative that suits what we want to believe, instead of what has really happened.

承认错误很难。从宏观层面来看,我们更容易自欺欺人地认为自己是对的,而从微观层面来看则不然,因为在微观层面我们能够直接看到和感受到后果。从宏观层面来看,我们脱离了情境的直接影响,自我意识就会介入,编造出一个符合我们自身意愿而非事实的叙事。

These flaws are the main reasons we keep repeating the same mistakes, and why we need to keep our feet on the ground as much as we can. As Confucius reportedly said, “A man who has committed a mistake and doesn’t correct it, is committing another mistake.”

这些缺陷是我们不断重复犯同样错误的主要原因,也是我们为何需要尽可能保持脚踏实地的原因。正如孔子所说:“犯错而不改正,就是犯另一个错。”

Most of the time, we don’t even perceive whatever conflicts with our beliefs. It’s much easier to go on thinking what we’ve already been thinking than go through the pain of updating our existing false beliefs. When it comes to seeing what is—that is, understanding reality—we can follow Charles Darwin’s advice to notice things “which easily escape attention” and ask why things happened. [5]

大多数时候,我们甚至不会察觉到与自身信念相冲突的事物。继续沿用已有的思维方式远比经历更新现有错误信念的痛苦要容易得多。说到看清事物的本来面目——也就是理解现实——我们可以遵循查尔斯·达尔文的建议,去留意那些“容易被忽略”的事物,并探究其发生的原因。[5]

We also tend to undervalue elementary ideas and overvalue complicated ones. This makes sense: Most of us get jobs based on some form of specialized knowledge. We don’t think we have much value if we know the things everyone else does, so we focus our effort on developing unique expertise to set ourselves apart. In an effort to ensure that our contributions are unique, we often end up rejecting simple solutions and focusing instead on complexity. But simple ideas are of great value because they can help us prevent complex problems.

我们往往低估简单的想法,高估复杂的想法。这不难理解:我们大多数人的工作都基于某种专业知识。如果我们掌握的知识人人都知道,就会觉得自己没什么价值,所以我们会集中精力发展独特的专长,让自己脱颖而出。为了确保自己的贡献独一无二,我们常常会放弃简单的解决方案,转而追求复杂。但简单的想法其实很有价值,因为它们可以帮助我们避免复杂问题的发生。

In identifying the Great Mental Models, we have looked for elementary principles, the ideas from multiple disciplines that form a timeless foundation for thought. It may seem bold to suggest that the same principles can improve everyone’s life, but the universe works in the same way no matter where you are in it. This is part of what makes the Great Mental Models so valuable—by understanding the principles, you can easily change tactics and apply the ones you need for your particular circumstances.

在探寻伟大思维模式的过程中,我们寻找的是基本原则,是来自多个学科的、构成永恒思想基础的理念。或许有人会觉得,认为同样的原则可以改善每个人的生活有些大胆,但无论你身处何方,宇宙的运行规律都是一样的。这正是伟大思维模式的价值所在——通过理解这些原则,你可以轻松调整策略,并根据自身情况选择合适的策略。

Most geniuses—especially those who lead others—prosper not by deconstructing intricate complexities but by exploiting unrecognized simplicities.

—Andy Benoit [6]

大多数天才——尤其是那些领导他人的天才——的成功并非源于解构错综复杂的问题,而是源于利用那些未被察觉的简单之处。——安迪·贝努瓦[6]

These elementary ideas, so often overlooked, come from multiple disciplines including biology, physics, chemistry, and more. They help us understand the interconnections of the world and see it for how it really is. This understanding in turn allows us to develop causal relationships, which allow us to match patterns, which allow us to draw analogies—all of this so we can navigate reality with clarity on the real dynamics involved.

这些常被忽视的基本概念源自生物学、物理学、化学等多个学科。它们帮助我们理解世界的相互联系,并看清世界的真实面貌。这种理解反过来又使我们能够建立因果关系,从而识别模式,进行类比——所有这一切,都是为了让我们能够清晰地了解现实中真实的动态变化,并以此驾驭现实。

Understanding Is Not Enough

仅仅理解是不够的

Understanding reality is not everything. The pursuit of understanding fuels meaning and adaptation, but this understanding by itself is not enough.

理解现实并非一切。追求理解能赋予意义并促进适应,但仅凭理解本身是不够的。

Understanding becomes useful only when we adjust our behavior and actions accordingly . The Great Mental Models are not just theory; they are actionable insights that can be used to create positive change in your life. What good is it to know that you constantly interrupt people, if you fail to adjust your behavior in light of this understanding? Granted, recognizing a mistake is easier than changing our behavior, since behavior patterns tend to be ingrained. It takes effort to change behavior, but your effort will be well spent. Don’t give up; change requires consistency. If you stick with it, you’ll see the fruits of your new understanding and its many downstream effects in real life.

只有当我们相应地调整自己的行为和行动时,理解才能真正发挥作用。伟大的心智模型并非仅仅是理论;它们是可操作的洞见,可以用来为你的生活带来积极的改变。如果你不根据这些理解调整自己的行为,那么即使你知道自己总是打断别人又有什么用呢?诚然,认识到错误比改变行为容易,因为行为模式往往根深蒂固。改变行为需要付出努力,但你的努力终将有所回报。不要放弃;改变需要坚持。如果你能坚持下去,你就会在现实生活中看到新理解带来的成果及其诸多后续影响。

Understand and Adapt or Fail

理解并适应,否则就会失败

Now you can see how we make suboptimal decisions and repeat mistakes: We are afraid to learn and to admit when we don’t know enough. This is the mindset that leads to poor initial decisions. These poor decisions are a source of stress and anxiety and consume massive amounts of time. Not when we’re making them—no, when we’re making them, they seem natural, because they align with how we want things to work.

现在你应该明白我们为什么会做出次优决策并重复犯错了吧:我们害怕学习,也害怕承认自己知识不足。正是这种心态导致了糟糕的初始决策。这些糟糕的决策会带来压力和焦虑,并耗费大量时间。然而,当我们做出这些决策时,它们似乎很自然——因为它们符合我们对事物发展的预期。

We get tripped up when the world doesn’t work the way we want it to or when we fail to see what is. We end up negotiating with reality, in a fight we are sure to lose; we think the world should work the way we want it to rather than the way it does. Instead of updating our views, we double down on our effort, accelerating our frustration and anxiety. It’s only weeks or months later, when we’re spending massive amounts of time fixing our mistakes, that we truly feel their weight. Then we wonder why we have no time for family and friends and why we’re so consumed by things outside of our control.

当世界没有按照我们预想的方式运转,或者我们看不清现实时,我们就会陷入困境。最终,我们不得不与现实讨价还价,而这场战斗我们注定会失败;我们认为世界应该按照我们想要的方式运转,而不是按照它实际运转的方式。我们不去更新自己的看法,反而加倍努力,加剧了挫败感和焦虑。只有几周或几个月后,当我们花费大量时间弥补错误时,才会真正感受到这些错误的沉重。这时,我们才会疑惑,为什么我们没有时间陪伴家人和朋友,为什么我们会如此被那些我们无法掌控的事情所困扰。

It’s easy to convince ourselves that these results stem from circumstances outside of our control. Even if that is partially true, it is not helpful. Passivity means that we rarely reflect on our previous decisions and attitudes and their outcomes. Without reflection, we cannot learn. [7] Without learning, we are doomed to repeat mistakes, become frustrated when the world doesn’t work the way we want it to, and wonder why we are falling further behind. The cycle goes on.

我们很容易说服自己,这些结果源于我们无法控制的外部因素。即便这部分属实,也无济于事。被动意味着我们很少反思过去的决定、态度及其后果。没有反思,我们就无法学习。[7] 没有学习,我们就注定要重蹈覆辙,当世界不如我们所愿时,我们会感到沮丧,并疑惑自己为何越落越远。如此循环往复。

Like it or not, we are not passive participants in our decision making. The world does not act on us as much as it reveals itself to us and we respond to it. We need to pay close attention to what’s happening. Ego gets in the way of this attention, locking reality behind a door that it controls with a gating mechanism. Only through persistence in the face of having the door slammed on us over and over can we begin to see the light on the other side.

无论你是否愿意,我们并非被动地参与决策。与其说世界对我们起作用,不如说世界向我们展现自身,而我们则对它做出反应。我们需要密切关注正在发生的一切。自我会阻碍这种关注,它用一种门禁机制将现实锁在一扇门后。只有一次又一次地被拒之门外,我们才能坚持不懈,最终看到门后的光明。

Ego usually works against us. It’s that part of the mind that’s always comparing and finding lack, fear, and unfairness. Things are never good enough for the ego. It always wants more—more money, more attention, more recognition. And sometimes it leads us to do reckless things to prove we are more. But whether ego is good or bad for you depends on the dose. In small amounts, ego is our friend.

自我通常会对我们产生负面影响。它是我们思维中那个总是与人比较、总在寻找不足、恐惧和不公的部分。对自我而言,一切都永远不够好。它总是想要更多——更多的金钱、更多的关注、更多的认可。有时,它甚至会驱使我们做出鲁莽的事情来证明自己更优秀。但是,自我究竟是好是坏,取决于它的程度。适度的自我,是我们的朋友。

If we had a perfect view of the world and made decisions rationally, we would never attempt to do the amazing things that make us human. Ego propels us. Why, without ego, would we even attempt to travel to Mars? After all, it’s never been done before. We’d never start a business, because most of them fail. We need to learn to understand when ego serves us and when it hinders us. When we strive more toward outcomes rather than personal status—especially if those outcomes benefit more people than ourselves—that’s a good use of ego.

如果我们对世界拥有完美的认知,并且能够理性地做出决定,我们就永远不会尝试去做那些让我们成为人的伟大壮举。是自我驱动着我们。如果没有自我,我们又怎会尝试登陆火星呢?毕竟,这在历史上从未有人做到过。我们也不会创办企业,因为大多数企业都会失败。我们需要学会分辨自我何时对我们有益,何时又会阻碍我们。当我们追求的是结果而非个人地位时——尤其当这些结果能够造福更多的人时——这才是对自我的正确运用。

Ego can be blinding when we optimize for short-term status protection over long-term happiness. This is the difference between being right and being effective. As we mature, our understanding of things turns from black-and-white to shades of gray. The world is smarter than we are and it will teach us all we need to know if we’re open to its feedback—if we keep our feet on the ground.

当我们为了短期地位的维护而牺牲长期的幸福时,自负就会蒙蔽我们的双眼。这就是正确与有效之间的区别。随着我们逐渐成熟,我们对事物的理解也会从非黑即白转变为灰色地带。世界比我们更智慧,如果我们愿意接受它的反馈——如果我们脚踏实地——它会教会我们所有需要知道的东西。

Mental Models and How to Use Them

心智模型及其运用方法

Perhaps an example will help illustrate the mental models approach. Think of gravity, something we learned about as kids and perhaps studied more formally in college as adults. We each have a mental model about gravity, whether we know it or not. That model helps us understand how gravity works. We don’t know all the details, but we know the basics.

或许举个例子能更好地说明心智模型的方法。想想重力,这是我们小时候就了解的,成年后可能在大学里也系统地学习过。我们每个人都对重力有一个心智模型,无论我们是否意识到这一点。这个模型帮助我们理解重力是如何运作的。我们并不了解所有细节,但我们掌握了基本原理。

Our model of gravity plays a fundamental role in our lives. It explains the movement of Earth around the sun. It informs the design of bridges and airplanes. It’s one of the models we use to evaluate the safety of leaning on a guardrail or repairing a roof. But we also apply our understanding of gravity in other, less obvious ways. We use the model as a metaphor to explain the influence of strong personalities, as when we say, “He was pulled into her orbit.” This is a reference to our basic understanding of the role of mass in gravity—the more there is, the stronger its pull. It also informs some classic sales techniques: Gravity diminishes with distance, and so too does your propensity to make an impulse purchase. Good salespeople know that the more distance you get, in time or geography, between yourself and the object of your desire, the less likely you are to buy it. Salespeople try to keep the pressure on, to get you to buy right away, before you can change your mind.

我们对引力的理解在我们的生活中扮演着至关重要的角色。它解释了地球绕太阳的运动,指导着桥梁和飞机的设计,也是我们用来评估倚靠护栏或维修屋顶安全性的模型之一。但我们对引力的理解也以其他一些不太明显的方式应用。我们用引力模型来比喻强势人物的影响,例如我们说“他被她吸引住了”。这指的是我们对质量在引力中作用的基本理解——质量越大,引力就越强。引力也影响着一些经典的销售技巧:引力会随着距离的增加而减弱,冲动购买的倾向也会随之降低。优秀的销售人员深谙此道:你与心仪之物之间的距离,无论是时间上的还是地理上的,越远,你购买的可能性就越小。销售人员会不断施压,让你在改变主意之前立即购买。

Gravity has been around since before humans, so we can consider it to be time-tested, reliable, and representative of reality. Our understanding of gravity—in other words, our mental model—lets us anticipate what will happen and helps us explain what has happened. We don’t need to be able to describe the physics in detail for the model to be useful.

引力在人类出现之前就已存在,因此我们可以认为它是经过时间考验的、可靠的,并且能够代表现实。我们对引力的理解——换句话说,我们的心理模型——使我们能够预测将会发生什么,并帮助我们解释已经发生的事情。我们并不需要能够详细描述其中的物理原理,这个模型就能发挥作用。

However, not every model is as reliable as gravity, and all models are flawed in some way. Some are reliable in some situations but useless in others. Some are too limited in their scope to be of much use. Others are unreliable because they haven’t been tested and challenged; yet others are just plain wrong. In every situation, we need to figure out which models are reliable and useful. We must also discard or update the unreliable ones, because unreliable or flawed models come with a cost.

然而,并非所有模型都像引力一样可靠,所有模型都存在缺陷。有些模型在某些情况下可靠,但在其他情况下却毫无用处。有些模型的适用范围过于有限,用途不大。有些模型不可靠,因为它们未经检验和验证;还有一些模型则完全错误。在任何情况下,我们都需要找出哪些模型可靠且有用。我们还必须摒弃或更新那些不可靠的模型,因为不可靠或有缺陷的模型会带来代价。

For a long time, people believed that bloodletting cured many different illnesses. This mistaken belief led doctors to contribute to the deaths of many of their patients. When we use flawed models, we are more likely to misunderstand the situation, the variables that matter, and the cause-and-effect relationships between those variables. Because of such misunderstandings, we often take suboptimal actions, like draining so much blood out of patients that they die of it.

长期以来,人们一直认为放血疗法可以治愈多种疾病。这种错误的观念导致许多医生造成了病人的死亡。当我们使用有缺陷的模型时,我们更容易误解实际情况、关键变量以及这些变量之间的因果关系。由于这些误解,我们常常采取次优措施,例如过度放血导致病人死亡。

Better models mean better thinking. The more accurately our models explain reality, the more they improve our thinking. Understanding reality is the name of the game. Understanding not only helps us decide which actions to take but helps us avoid actions that have a big downside that we otherwise would not be aware of. When we understand, not only do we see the immediate problem with more accuracy, we can also begin to see the second-, third-, and higher-order consequences of various choices. This understanding helps us eliminate avoidable errors. Sometimes, making good decisions boils down to avoiding bad ones.

更好的模型意味着更好的思维。我们的模型对现实的解释越准确,就越能提升我们的思维能力。理解现实至关重要。理解不仅能帮助我们决定采取哪些行动,还能帮助我们避免那些我们原本无法察觉的、具有巨大负面影响的行动。当我们理解时,不仅能更准确地看到眼前的问题,还能开始看到各种选择的第二、第三乃至更高层次的后果。这种理解有助于我们避免不必要的错误。有时,做出好的决策归根结底就是避免做出坏的决策。

Flawed beliefs, regardless of the intentions behind them, cause harm when they are put into action. When it comes to applying mental models, we tend to run into trouble either when our model of reality is wrong—that is, it doesn’t survive real-world experience—or when our model is right, but we apply it to a situation where it doesn’t belong.

无论其背后的意图如何,错误的信念一旦付诸实践,就会造成伤害。在运用思维模型时,我们往往会遇到两种情况:一是我们的现实模型本身就是错误的——也就是说,它经不起现实世界经验的检验;二是我们的模型本身是正确的,但我们却将其应用于不适用的情境中。

Models that don’t hold up to reality cause mistakes. The model of bloodletting caused unnecessary deaths because it weakened patients when they needed all their strength to fight their illnesses. It hung around for such a long time because it was part of a package of flawed models, such as ones explaining the causes of sickness and how the human body worked, that made it difficult to determine exactly where the bloodletting model didn’t fit with reality.

不符合现实的模型会导致错误。放血疗法模型造成了不必要的死亡,因为它削弱了患者的身体,而患者当时最需要的是集中精力对抗疾病。该模型之所以长期存在,是因为它与其他一些存在缺陷的模型(例如解释疾病成因和人体运作机制的模型)一起,使得人们难以准确判断放血疗法模型究竟在哪些方面与现实不符。

We compound the problem of flawed models when we fail to update our models after evidence indicates they are wrong. Only by repeatedly testing our models against reality and being open to feedback can we update our understanding of the world and change our thinking. We need to look at the results of applying a model over the largest sample size of problems possible to be able to refine it so that it aligns with how the world actually works.

当我们发现模型存在缺陷后却不及时更新时,就会加剧模型本身的缺陷问题。只有反复用现实检验模型,并虚心接受反馈,我们才能更新对世界的理解,转变思维方式。我们需要尽可能多地分析模型在实际问题中的应用结果,才能不断完善模型,使其与世界的实际运行规律相符。

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The Power of Acquiring New Models

获取新模型的力量

The quality of our thinking depends to a large extent on the mental models in our head. While we want useful models, we also want a wide variety of models to help us uncover what’s really happening. Most of us study something specific and don’t get exposure to the big ideas of other disciplines; we don’t develop the multidisciplinary mindset that we need to accurately see a problem. And because we don’t have the right models to understand the situation, we overuse the models we do have, applying them even where they don’t belong.

我们思维的质量很大程度上取决于我们头脑中的心智模型。我们固然需要实用的模型,但也需要各种各样的模型来帮助我们揭示事物的真相。我们大多数人学习的是某个特定领域,很少接触到其他学科的核心思想;我们没有培养出准确看待问题所需的跨学科思维。正因为我们缺乏理解现状的合适模型,我们才会过度依赖现有的模型,甚至在不适用的领域也应用它们。

You’ve likely experienced this firsthand: An engineer will often think in terms of systems by default. A psychologist will think in terms of incentives. A businessperson might think in terms of opportunity cost and risk-reward calculation. Through their respective lenses, each person sees part of the situation, the part of the world that makes sense to them. None of them, however, sees the entire situation unless they are thinking in a multidisciplinary way. In short, they have blind spots—big ones. And they’re not aware of their blind spots. There is an adage that encapsulates this idea: “To the man with only a hammer, everything starts looking like a nail.” Not every problem is a nail. The world is full of complications and interconnections that can only be explained through understanding multiple models.

你可能对此深有体会:工程师通常会默认从系统角度思考问题;心理学家会从激励机制的角度思考问题;商人则会考虑机会成本和风险回报计算。透过各自的视角,每个人都能看到问题的一部分,看到他们认为有意义的世界。然而,除非他们采用跨学科的思维方式,否则他们都无法看到问题的全貌。简而言之,他们都存在盲点——而且是很大的盲点。他们往往意识不到自己的盲点。有一句谚语恰如其分地概括了这一点:“对于一个只有锤子的人来说,所有东西看起来都像钉子。”并非所有问题都是钉子。世界充满了错综复杂的关系,只有通过理解多种模型才能解释这一切。

Removing blind spots means thinking through the problem using different lenses or models. When we do this, our blind spots slowly go away, and we gain a more complete understanding of the problem.

消除盲点意味着运用不同的视角或模型来思考问题。当我们这样做时,我们的盲点会逐渐消失,我们对问题的理解也会更加全面。

Consider the parable of the blind men encountering an elephant for the first time, trying to understand it by touch. The first person, whose hand touches the trunk, says, “This creature is like a thick snake.” For the second person, whose hand finds an ear, the elephant seems like a type of fan. The third person, whose hand is on a leg, says the elephant is a pillar, like a tree trunk. The fourth blind man, who places his hand on the creature’s side, says, “An elephant is a wall.” The fifth, who feels its tail, describes it as a rope. The last blind man touches a tusk and states that the elephant is something that is hard and smooth, like a spear. They are all right—yet they are also all wrong.

想想盲人摸象的寓言。第一个盲人摸到象鼻,说:“这东西像一条粗蛇。”第二个盲人摸到象耳,觉得大象像一把扇子。第三个盲人摸到象腿,说大象像一根柱子,像树干。第四个盲人摸到象身,说大象像一堵墙。第五个盲人摸到象尾,说大象像一根绳子。最后一个盲人摸到象牙,说大象又硬又光滑,像一根矛。他们都说对了,但又都错了。

We’re much like the blind men in the classic parable, going through life trying to explain everything through our one limited lens of perspective. Too often that lens is driven by our particular field of expertise, be it economics, engineering, physics, mathematics, biology, chemistry, or something else entirely. Each of these disciplines holds some truth, and yet none of them contains the whole truth.

我们就像经典寓言中的盲人,一生都在试图用自己有限的视角去解释一切。而这种视角往往受到我们特定专业领域的制约,无论是经济学、工程学、物理学、数学、生物学、化学,还是其他任何学科。每个学科都蕴含着一定的真理,但没有哪个学科能够涵盖全部真理。

Here’s another way to look at it: Think of a forest. When a botanist looks at a forest, they focus on the ecosystem. An environmentalist sees the impact of climate change, a forest engineer the state of the trees’ growth, a businessperson the commercial value of the land. None is wrong, but neither is any of them able to describe the full scope of the forest. Sharing knowledge, or learning the basics of other disciplines, would lead them to a more well-rounded understanding that would allow for better decisions about managing the forest.

换个角度来看:想想一片森林。植物学家观察森林时,关注的是生态系统;环保主义者关注气候变化的影响;森林工程师关注树木的生长状况;商人关注土地的商业价值。他们各自的关注点都没有错,但他们都无法全面描述森林的全貌。分享知识,或者学习其他学科的基础知识,可以帮助他们更全面地了解森林,从而做出更明智的森林管理决策。

A lot of people start out with 400-horsepower motors but only get a hundred horsepower of output. It’s way better to have a 200-horsepower motor and get it all into output.

—Warren Buffett [9]

很多人一开始就买400马力的发动机,但实际输出功率只有100马力。还不如买200马力的发动机,把所有动力都用在发动机输出上。——沃伦·巴菲特[9]

Relying on only a few models is like having a four-hundred-horsepower brain that’s generating only fifty horsepower of output. To increase your mental efficiency and reach your four-hundred-horsepower potential, you need to use Charlie Munger’s latticework of mental models. Exactly the same sort of pattern that graces backyards everywhere, a lattice is a series of points that connect to and reinforce each other. The Great Mental Models can be understood in the same way—models influence and interact with each other to create a structure that can be used to evaluate and understand ideas.

仅仅依赖少数几个模型,就像拥有400马力的大脑却只能发挥50马力一样。为了提升思维效率,充分发挥400马力的潜能,你需要运用查理·芒格的思维模型网络。这种网络结构就像随处可见的花园图案,由一系列相互连接、相互强化的点组成。理解“伟大的思维模型”也是如此——不同的模型相互影响、相互作用,最终构建出一个可以用来评估和理解各种想法的框架。

In a famous speech he gave in the 1990s, Munger summed up his approach to practical wisdom: “Well, the first rule is that you can’t really know anything if you just remember isolated facts and try and bang ’em back. If the facts don’t hang together on a latticework of theory, you don’t have them in a usable form. You’ve got to have models in your head. And you’ve got to array your experience—both vicarious and direct—on this latticework of models. You may have noticed students who just try to remember and pound back what is remembered. Well, they fail in school and in life. You’ve got to hang experience on a latticework of models in your head.” [10]

在20世纪90年代的一次著名演讲中,芒格总结了他对实践智慧的理解:“首先,如果你只是记住一些孤立的事实,然后试图生搬硬套地复述出来,你就无法真正了解任何事情。如果这些事实不能被整合到一个理论框架中,它们就无法被运用。你必须在脑海中构建模型。你必须将你的经验——无论是间接的还是直接的——都建立在这个模型框架之上。你可能注意到有些学生只是试图记住并生搬硬套地复述所记住的内容。结果,他们在学校和生活中都失败了。你必须将经验建立在你脑海中的模型框架之上。”[10]

The chief enemy of good decisions is a lack of sufficient perspectives on a problem.

—Alain de Botton [11]

良好决策的最大敌人是对问题缺乏充分的视角。——阿兰·德波顿[11]

Expanding Your Latticework of Mental Models

拓展你的思维模型网络

A latticework is an excellent way to conceptualize mental models because it demonstrates the reality and value of interconnecting knowledge. The world does not isolate itself into discrete disciplines. We break it down that way only because it makes it easier to study it. Once we learn something, we need to put it back into the complex system in which it occurs. We need to see where it connects to other bits of knowledge, to build our understanding of the whole. This is the value of putting the knowledge contained in mental models into a latticework.

网格图是构建心智模型的一种绝佳方式,因为它展现了知识相互关联的真实性和价值。世界并非孤立地存在于各个独立的学科之中。我们之所以将其划分成不同的学科,仅仅是因为这样便于研究。一旦我们学习了某些知识,就需要将其重新融入到它所处的复杂系统中。我们需要了解它与其他知识之间的联系,从而构建对整体的理解。这正是将心智模型中包含的知识构建成网格图的价值所在。

Our latticework reduces the blind spots that limit our view of not only the immediate problem but also the second- and subsequent-order effects of our potential solutions. Without a latticework of the Great Mental Models, our decisions become harder, slower, and less creative. By using a mental models approach, by being curious about how the rest of the world works, we can complement our specializations. A quick glance at the lists of Nobel Prize winners shows that many of them, obviously extreme specialists in something, had multidisciplinary interests that supported their achievements.

我们的思维框架能够减少盲点,这些盲点不仅限制了我们对当前问题的理解,也限制了我们对潜在解决方案的二阶及后续影响的洞察。如果没有这种由伟大思维模型构成的框架,我们的决策就会变得更加困难、缓慢且缺乏创造力。通过运用思维模型的方法,通过对世界其他领域运作方式的好奇心,我们可以弥补自身专业领域的不足。只需快速浏览一下诺贝尔奖得主名单,我们就会发现,许多获奖者虽然在某个领域显然是顶尖专家,但他们也拥有跨学科的兴趣,而这些兴趣也为他们取得的成就提供了支持。

To help you build your own latticework of mental models, this book, and the volumes that follow, will attempt to arm you with the big models from multiple disciplines. We’ll look at biology, physics, chemistry, economics, and even psychology. We don’t need to master all the details from these disciplines, just the fundamentals.

为了帮助你构建自己的思维模型体系,本书及后续章节将尝试为你提供来自多个学科的宏观模型。我们将探讨生物学、物理学、化学、经济学,甚至心理学。我们无需掌握这些学科的所有细节,只需掌握其基本原理即可。

To quote Charlie Munger, “Eighty or ninety important models will carry about 90 percent of the freight in making you a worldly-wise person. And, of those, only a mere handful really carry very heavy freight.” [12]

用查理·芒格的话来说,“八九十个重要的模型可以让你成为一个世故的人,并带给你大约 90% 的收获。而其中,只有极少数模型真正承载着非常沉重的负担。”[12]

The four volumes of The Great Mental Models attempt to collect and make accessible organized common sense—the eighty to ninety mental models you need from the major disciplines to get started. To help you understand the models, we will relate them to stories and historical examples. My blog, Farnam Street , will have even more practical examples (see https://fs.blog/mental-models/ ).

《伟大的心智模型》四卷本旨在收集并整理常识,为你提供入门所需的八九十个来自主要学科的心智模型。为了帮助你理解这些模型,我们将结合故事和历史案例进行讲解。我的博客“法纳姆街”(Farnam Street)上会有更多实用案例(参见https://fs.blog/mental-models/)。

The more high-quality mental models you have in your mental toolbox, the more likely you will have the ones needed to understand a given problem. The better you understand, the better the potential actions you can take. The better the potential actions, the fewer problems you’ll encounter down the road. Better models make better decisions.

你的思维工具箱里拥有的高质量思维模型越多,你就越有可能拥有理解特定问题所需的模型。理解得越透彻,你能采取的行动就越有效。行动越有效,未来遇到的问题就越少。更好的模型造就更好的决策。

I think it is undeniably true that the human brain must work in models. The trick is to have your brain work better than the other person’s brain because it understands the most fundamental models: ones that will do the most work per unit. If you get into the mental habit of relating what you’re reading to the basic structure of the underlying ideas being demonstrated, you gradually accumulate some wisdom.

—Charlie Munger [13]

我认为,人脑必须以模型的方式运作,这一点毋庸置疑。关键在于,如何让你的大脑比别人的大脑运作得更好,因为它理解最基本的模型:那些单位时间内能做最多工作的模型。如果你养成将所读内容与所论证的基本概念结构联系起来的思维习惯,你就会逐渐积累智慧。——查理·芒格[13]

Time Invested Yields Enormous Benefits

投入的时间会带来巨大的收益

Successful people file away a collection of fundamental, established, essentially unchanging knowledge that can be used in evaluating the infinite number of unique scenarios that show up in the real world. Each decision presents an opportunity to comb through your repertoire of models and try one out, so you can learn how to use them. This will slow you down at first—for one thing, you won’t always choose the right models—but you will get better and more efficient at using mental models as time progresses.

成功人士会积累一系列基础的、成熟的、基本不变的知识,用于评估现实世界中出现的各种独特情况。每一个决策都是一次机会,让你梳理自己的模型库并尝试使用其中一个,从而学习如何运用它们。起初这可能会拖慢你的速度——首先,你不可能总是选择正确的模型——但随着时间的推移,你会越来越熟练、越来越高效地运用这些思维模型。

Disciplines, like nations, are a necessary evil that enable human beings of bounded rationality to simplify their goals and reduce their choices to calculable limits. But parochialism is everywhere, and the world badly needs international and interdisciplinary travelers to carry new knowledge from one enclave to another.

—Herbert A. Simon [14]

学科如同国家一样,是一种必要的恶,它使理性有限的人类能够简化目标,并将选择限制在可计算的范围内。然而,狭隘主义无处不在,世界迫切需要国际化和跨学科的交流者,将新知识从一个领域传播到另一个领域。——赫伯特·A·西蒙[14]

With time and consistent effort, we begin to synthesize the ideas we learn with reality itself . No model contains the entire truth, whatever that may be. What good are math and biology and psychology unless we know how they fit together in reality, and how to use them to make our lives better? It would be like dying of hunger because we don’t know how to combine and cook any of the foods in our pantry.

随着时间和持续努力,我们开始将所学知识与现实本身结合起来。没有任何模型能够包含全部真理,无论真理是什么。如果我们不知道数学、生物学和心理学如何在现实中相互关联,以及如何运用它们来改善我们的生活,那么这些知识又有什么用呢?这就像因为我们不知道如何烹饪和搭配储藏室里的任何食材而饿死一样。

Making mistakes is part of the process of using mental models. Failing, if you acknowledge, reflect on, and learn from it, is also how you build mastery. As you use mental models, a great practice is to record and reflect on your process and results. That way, you can get better at both choosing models and applying them. Take the time to notice how you applied the models, what the process was like, and what the results were.

犯错是运用心智模型过程中不可避免的一部分。如果你能正视失败、反思并从中吸取教训,失败也是你精进技艺的途径。在使用心智模型时,一个很好的做法是记录并反思你的过程和结果。这样,你就能更好地选择和运用心智模型。花些时间留意你是如何运用这些模型的,整个过程是怎样的,以及最终的结果如何。

Over time, you will develop your knowledge of which situations are best tackled through which models. Don’t give up on a model if it doesn’t help you right away. Learn more about it and try to figure out exactly why it didn’t work. It may be that you have to improve your understanding of it, or that there were aspects to the situation that you did not consider, or that your focus was on the wrong variable. So keep a journal. Write down your experiences. When you identify a model at work in the world, write that down too. Then you can explore the applications you’ve observed and start to be more in control of the models you use every day. For instance, instead of falling victim to confirmation bias, you will become able to step back and see it at work in yourself and others. Once you get practice with them, you will start to naturally apply models as you go through your daily life, from reading the news to contemplating a career move.

随着时间的推移,你会逐渐了解哪些情况最适合用哪些模型来应对。如果某个模型一开始没有帮到你,不要轻易放弃。深入了解它,并尝试找出它失效的真正原因。或许你需要加深对它的理解,或许你忽略了某些方面,又或许你关注的变量错了。所以,不妨记日记,记录你的经历。当你发现某个模型在现实生活中发挥作用时,也要把它记录下来。这样,你就可以探索你观察到的应用,并开始更好地掌控你日常使用的模型。例如,你将不再受确认偏差的影响,而是能够跳出固有思维,看到它在你自身和他人身上是如何运作的。一旦你熟练掌握了这些模型,你就会自然而然地将它们运用到日常生活中,从阅读新闻到思考职业发展方向,无所不包。

As we have seen, we can run into problems when we apply models to situations in which they don’t fit. If a model is useful—and we can define “useful,” here, as offering a different perspective that uncovers a blind spot in our understanding of a problem—it is wise to invest time and energy into understanding why it worked, so we know when to use it again.

正如我们所见,当模型被应用于不适用的情境时,就会出现问题。如果一个模型是有用的——在这里,我们可以将“有用”定义为提供一种不同的视角,揭示我们对问题理解中的盲点——那么明智的做法是投入时间和精力去理解它为何有效,以便我们知道何时再次使用它。

At the beginning, the process is more important than the outcome. As you use the models, stay open to feedback loops. Reflect and learn. You will get better. It will become easier. Results will become more profoundly useful, more broadly applicable, and more memorable. While this book isn’t intended to be a book specifically about making better decisions, it will help you make better decisions.

一开始,过程比结果更重要。在使用模型的过程中,要保持开放的心态,接受反馈。反思并学习。你会不断进步,一切都会变得更容易。结果也会变得更有意义、更广泛适用、更令人难忘。虽然本书并非专门教你如何做出更好的决策,但它确实能帮助你做出更好的决策。

Mental models are not an excuse to create a lengthy decision process. Rather, their aim is to help you move away from seeing things the way you think they should be and toward seeing them the way they are. Right now, you are touching only one part of the elephant, so you are making all decisions based on your understanding that it’s a wall, or a rope, not an animal. As soon as you begin to take in the knowledge that other people have of the world, like learning the perspectives others have on the elephant, you will start having more success, because your decisions will be aligned with how the world really is.

心智模型并非冗长决策过程的借口。相反,它的目的是帮助你摆脱“事物应该是什么样子”的固有观念,转而以事物本来的样子去看待它们。此刻,你只触及了大象的一部分,因此你所有的决定都基于你对它的理解——它只是一堵墙或一根绳子,而非一头真正的动物。一旦你开始吸收他人对世界的认知,例如了解他人对大象的看法,你就会取得更大的成功,因为你的决策将与世界的真实面貌相符。

When you start to understand the world better, when the whys become less mysterious, you will gain confidence in how you navigate. Successes will accrue. More success means more time, less stress, and, ultimately, a more meaningful life.

当你开始更好地了解这个世界,当那些“为什么”不再神秘莫测时,你就会在应对一切时建立起自信。成功会接踵而至。更多的成功意味着更多的时间、更少的压力,最终,也意味着更有意义的人生。

Time to dive in.

是时候下水了。

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The Map Is Not the Territory

地图并非疆域本身

Reality check.

认清现实。

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Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.

—George E. P. Box [1]

记住,所有模型都是不完美的;实际问题在于,它们要错到什么程度才算毫无用处。——乔治·E·P·博克斯[1]
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The map of reality is not reality. Even the best maps are imperfect. That’s because maps are reductions of what they represent. If a map were to represent the territory with perfect fidelity, it would no longer be a reduction and thus would no longer be useful to us. A map can also be a snapshot from a point in time, representing something that no longer exists. This is important to keep in mind as we think through problems and seek to make better decisions.

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现实的地图并非现实本身。即使是最好的地图也并非完美无缺。这是因为地图是对所代表事物的简化。如果地图能够完美地展现整个区域,它就不再是简化,也就失去了意义。地图也可能只是某个时间点的快照,代表着早已不复存在的事物。在思考问题和寻求更佳决策时,牢记这一点至关重要。

We use maps every day to simplify complexity. A great example is the financial statements of a company, which are meant to distill the complexity of thousands of transactions into something manageable. Yet they tell us nothing about whether the product is good for the customer or what’s really going on in the company. A policy document on office procedure, a manual on parenting a two-year-old, or your performance review—all are models, or maps, that simplify some complex territory to guide you through it.

我们每天都在使用地图来简化复杂情况。一个很好的例子就是公司的财务报表,它旨在将成千上万笔交易的复杂性提炼成易于理解的内容。然而,财务报表并不能告诉我们产品是否对客户有益,也不能告诉我们公司内部的真实情况。一份关于办公流程的政策文件、一本关于如何养育两岁孩子的育儿手册,或者你的绩效考核——所有这些都是模型或地图,它们简化了某些复杂的领域,引导你顺利完成任务。

Relying solely on maps can lead you to the wrong conclusion. You need to touch the territory.

仅仅依靠地图可能会得出错误的结论。你需要实地考察。

Very early in the history of Amazon, Jeff Bezos was going over a set of documents with his team at the weekly business review. He’d heard that a bunch of customers were complaining (the territory) about call wait times, and yet looking at the data (the map), he couldn’t figure out why. “When the data and the anecdotes disagree,” he said in an interview, “the anecdotes are usually right.” [2] At the meeting, the head of customer service reported the wait-time metric as under sixty seconds, which was in line with expectations. Bezos paused the meeting, picked up the phone, and dialed the 1-800 number for customer service. He waited on hold for over ten minutes, which made the point: something was wrong with the data collection.

在亚马逊创立初期,杰夫·贝佐斯在每周的业务回顾会议上与团队一起查看一系列文件。他听说很多客户都在抱怨电话等待时间过长,但查看数据后,他却找不到原因。“当数据和客户反馈不一致时,”他在一次采访中说道,“通常情况下,客户反馈才是正确的。”[2] 会议上,客服主管报告说等待时间低于60秒,符合预期。贝佐斯暂停了会议,拿起电话拨打了客服热线1-800。他等了十多分钟才接通,这说明问题出在数据收集上:数据收集肯定有问题。

Mental models are maps. While they might not be perfectly accurate, they are useful. Mental models and maps are both useful to the extent they are explanatory and predictive.

心理模型就像地图。虽然它们可能并不完全精确,但却很有用。心理模型和地图的实用性都体现在它们解释和预测的能力上。

Key Elements of a Map

地图的关键要素

In 1931, the mathematician Alfred Korzybski presented a paper on mathematical semantics in New Orleans. Most of the paper reads like a complex, technical argument on the relationship of mathematics to human language, and of both of these to physical reality. However, with this paper, Korzybski introduced and popularized the concept that the map is not the territory— in other words, the description of the thing is not the thing itself. The model is not reality. The abstraction is not the abstracted.

1931年,数学家阿尔弗雷德·科日布斯基在新奥尔良发表了一篇关于数学语义学的论文。论文的大部分内容读起来像是一篇复杂而专业的论证,探讨了数学与人类语言之间的关系,以及二者与物理现实之间的关系。然而,正是通过这篇论文,科日布斯基提出并普及了“地图并非疆域”这一概念——换句话说,对事物的描述并非事物本身。模型并非现实。抽象并非被抽象之物。

Specifically, in Korzybski’s own words: [3]

具体来说,用科尔日布斯基自己的话说:[3]

  1. A map may have a structure similar or dissimilar to the structure of the territory. The London Underground map is super useful to travelers. The train drivers don’t use it at all! Maps describe a territory in a useful way, but with a specific purpose in mind. They cannot be everything to everyone.

    地图的结构可能与实际区域的结构相似,也可能不同。伦敦地铁图对旅行者来说非常有用,但火车司机却完全不用它!地图以一种实用的方式描述一个区域,但其目的都是为了服务于特定的用途。地图不可能满足所有人的所有需求。

  2. Two similar structures have similar logical characteristics. If a correct map shows Dresden as located between Paris and Warsaw, a similar relation is found in the actual territory. If you have a map showing where Dresden is, you should be able to use it to get there.

    两个相似的结构具有相似的逻辑特征。如果一张正确的地图显示德累斯顿位于巴黎和华沙之间,那么在实际的地理区域内也存在类似的关联。如果你有一张标明德累斯顿位置的地图,你应该能够利用它找到那里。

  3. A map is not the actual territory. The London Underground map does not convey what it’s like to be standing in Covent Garden Station, nor would you use it to navigate out of the station.

    地图并非实际的地理区域。伦敦地铁地图并不能展现你站在科文特花园站时的感受,你也不会用它来指引你走出车站。

  4. An ideal map would contain the map of the map, the map of the map of the map, etc., endlessly. We may call this characteristic self-reflexiveness. Imagine using an overly complicated “Guide to Paris” on a trip to France, and then having to purchase another book, the “Guide to the Guide to Paris,” and so on. Ideally, you’d never have any issues—but eventually, the level of detail would be overwhelming.

    一张理想的地图应该包含地图的地图,地图的地图的地图,如此层层嵌套,永无止境。我们可以称这种特性为自反性。想象一下,你去法国旅行时使用了一本过于复杂的《巴黎旅游指南》,之后又不得不购买另一本书——《巴黎旅游指南指南》,以此类推。理想情况下,你不会遇到任何问题——但最终,细节之多会让你不堪重负。

The only way we can navigate the complexity of the world is through some sort of abstraction. When we read the news, we’re consuming abstractions of events created by other people. The authors consumed vast amounts of information, reflected upon it, and drew some conclusions that they share with us. But something is also lost in the process: the specific and relevant details that were compressed into the abstraction. And, because we often consume these abstractions as gospel, without having done the hard mental work of creating them ourselves, it’s tricky for us to see when the map no longer agrees with the territory. We inadvertently forget that the map is not reality. It’s the illusion of knowledge.

我们理解复杂世界的唯一途径就是某种抽象化。当我们阅读新闻时,我们实际上是在吸收他人对事件的抽象概括。新闻作者们吸收了大量信息,经过思考和分析,得出了一些结论并与我们分享。但在这个过程中,也丢失了一些东西:那些被压缩成抽象概括的具体而相关的细节。而且,由于我们常常把这些抽象概括奉为真理,而没有像其他人那样进行过艰苦的思考和构建,因此我们很难察觉到当抽象概括与实际情况不符时。我们不经意间忘记了,抽象概括并非现实,它只是知识的幻象。

But My GPS Didn’t Show That Cliff

但我的GPS没显示那座悬崖

We need maps and models as guides. But frequently, we don’t remember that our maps and models are abstractions, and thus we fail to understand their limits. We forget there is a territory that exists separately from the map. This territory contains details the map doesn’t describe. We run into problems when our knowledge becomes knowledge of the map rather than of the actual underlying territory it describes.

我们需要地图和模型作为指南。但我们常常忘记,地图和模型都是抽象概念,因此无法理解它们的局限性。我们忘记了地图之外还存在着一个独立的领域。这个领域包含着地图无法描绘的细节。当我们的知识仅仅局限于地图本身,而非它所描述的实际领域时,问题就出现了。

Reality is messy and complicated, so our tendency to simplify it is understandable. However, if the aim becomes simplification rather than understanding, we start to make bad decisions. When we mistake the map for the territory, we start to think we have all the answers. We create static rules or policies that deal with the map but forget that we exist in a constantly changing world. When we close off or ignore feedback loops, we don’t see that the terrain has changed and we dramatically reduce our ability to adapt to a changing environment.

现实纷繁复杂,我们倾向于将其简化,这可以理解。然而,如果我们追求的是简化而非理解,就会开始做出错误的决定。当我们把地图误认为实际的地形时,就会觉得自己掌握了所有答案。我们制定静态的规则或政策来应对地图上的景象,却忘记了我们身处一个不断变化的世界。当我们关闭或忽略反馈回路时,我们就看不到地形的变化,从而大大降低了我们适应环境变化的能力。

We can’t use maps as dogma. Maps and models are not meant to live forever as static references. The world is dynamic. As territories change, our tools to navigate them must be flexible, to handle a wide variety of situations or adapt to the changing times. If the value of a map or model is related to its ability to predict or explain, then it needs to represent reality. If reality has changed, the map must change.

我们不能把地图当作教条。地图和模型并非旨在作为静态参考而永远存在。世界是动态的。随着地域的变化,我们用来导航的工具也必须灵活,以应对各种情况或适应时代的变化。如果地图或模型的价值在于其预测或解释的能力,那么它就必须反映现实。如果现实发生了变化,地图也必须随之改变。

Take Newtonian physics. For hundreds of years, it served as an extremely useful model for understanding the workings of our world. From gravity to celestial motion, Newtonian physics was a wide-ranging map.

以牛顿物理学为例。数百年来,它一直是理解世界运行规律的极其有用的模型。从万有引力到天体运动,牛顿物理学涵盖范围极广。

Then, in 1905, Albert Einstein, with his theory of special relativity, changed our understanding of the universe in a huge way. He replaced the understanding handed down by Isaac Newton hundreds of years earlier. He created a new map.

1905年,阿尔伯特·爱因斯坦凭借狭义相对论,彻底改变了我们对宇宙的理解。他取代了数百年前艾萨克·牛顿留下的认知,绘制了一幅全新的宇宙地图。

Newtonian physics is still a very useful model. One can use it reliably to predict the movement of objects large and small (with some limitations, as pointed out by Einstein). And, on the flip side, Einstein’s physics is still not totally complete: with every year that goes by, physicists become increasingly frustrated with their inability to tie it into small-scale quantum physics. Another map may yet come. But what physicists do so well, and most of us do so poorly, is carefully delimit what Newtonian and Einsteinian physics are able to explain. They know, down to many decimal places, where those maps are useful guides to reality and where they aren’t. And when they hit uncharted territory, like quantum mechanics, they explore it carefully, instead of assuming the maps they have can explain it all.

牛顿物理学仍然是一个非常有用的模型。人们可以用它来可靠地预测大小物体的运动(当然,正如爱因斯坦指出的那样,它也存在一些局限性)。另一方面,爱因斯坦的物理学也并非完全完善:随着时间的推移,物理学家们越来越沮丧于他们无法将其与小尺度量子物理学联系起来。或许未来还会出现新的理论框架。但物理学家们做得非常出色,而我们大多数人却做得非常糟糕的地方在于,他们能够精确地界定牛顿物理学和爱因斯坦物理学能够解释的范围。他们非常清楚,精确到小数点后很多位,这些理论框架在哪些情况下能够有效地指导我们理解现实,在哪些情况下则不然。当他们遇到未知的领域,例如量子力学时,他们会谨慎地进行探索,而不是想当然地认为他们已有的理论框架可以解释一切。

Maps Can’t Show Everything

地图无法显示所有内容

Some of the biggest map/territory problems are the risks of the territory that are not shown on the map. When we’re following the map without looking around, we trip right over these risks. Any user of a map or model must realize that we do not understand a model, map, or reduction unless we understand and respect its limitations. If we don’t understand what the map does and doesn’t tell us, it can be useless or even dangerous.

地图/地形图最大的问题之一,就是地图上未显示的地形风险。如果我们只看地图而不观察周围环境,就很容易被这些风险绊倒。任何地图或模型的使用者都必须意识到,如果我们不理解并尊重其局限性,就无法真正理解模型、地图或简化过程。如果我们不理解地图能告诉我们什么、不能告诉我们什么,它就可能毫无用处,甚至会带来危险。

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Economist Elinor Ostrom wrote about being cautious with maps and models when looking at different governance structures for common resources. She was worried that the Tragedy of the Commons model (see sidebar), which shows how a shared resource can be destroyed through bad incentives, was too general and did not account for how people, in reality, solved the problem. She explained the limitations of using models to guide public policy, namely, that they often become metaphors: “What makes these models so dangerous…is that the constraints that are assumed to be fixed for the purpose of analysis are taken on faith as being fixed in empirical settings.” [6]

经济学家埃莉诺·奥斯特罗姆(Elinor Ostrom)曾撰文指出,在研究公共资源的不同治理结构时,应谨慎使用地图和模型。她担心“公地悲剧”模型(见侧边栏)过于笼统,未能解释人们在现实中是如何解决问题的。该模型展示了不良激励机制如何破坏共享资源。她解释了使用模型指导公共政策的局限性,即模型常常沦为隐喻:“这些模型的危险之处在于……为了分析目的而假定的固定约束,被想当然地认为在实际环境中也同样固定不变。”[6]

This is a double problem. First, having a general map, we may assume that if a territory matches the map in a couple of respects, it matches the map in all respects. Second, we may cling to what we know rather than update our information; we may think adherence to the map is more important than taking in new information about a territory. Ostrom asserts that one of the main values of using models as maps in public policy discussions is in the thinking that is generated. Models are tools for exploration, not doctrines to force conformity. They are guidebooks, not laws.

这是一个双重问题。首先,有了总体地图,我们可能会想当然地认为,如果某个地区在某些方面与地图相符,那么它在所有方面也都与地图相符。其次,我们可能会固守已知信息,而不是更新信息;我们可能会认为遵循地图比了解该地区的新信息更重要。奥斯特罗姆认为,在公共政策讨论中使用模型作为地图的主要价值之一在于它所激发出的思考。模型是探索的工具,而不是强制服从的教条。它们是指南,而不是法律。

In order to use a map or model as accurately as possible, we should take into account three important principles:

为了尽可能准确地使用地图或模型,我们应该考虑以下三个重要原则:

  1. Reality is the ultimate update.

    现实才是最终的更新。

  2. Consider the cartographer.

    想想制图师。

  3. Maps can influence territories.

    地图可以影响领土范围。

Reality is the ultimate update: When we enter new and unfamiliar territory, it’s nice to have a map on hand. In everything from traveling to a new city to becoming a parent for the first time, we benefit from maps that we can use to improve our ability to navigate the terrain. But territories change, sometimes faster than the maps and models that describe them. We can and should update our maps based on our own experiences in the territory. That’s how good maps are built: through feedback loops created by explorers.

现实才是最终的更新:当我们进入陌生的新领域时,手边有一张地图总是有益的。无论是前往一座新城市,还是初为人父母,我们都能从地图中获益,提升应对各种情况的能力。然而,领域瞬息万变,有时甚至比描述它们的地图和模型更新得更快。我们可以也应该根据自身在该领域的经验来更新地图。好的地图正是通过探索者们不断积累的反馈循环而构建的。

We can think of stereotypes as maps. Sometimes they are useful—we have to process large amounts of information every day, and simplified chunks such as stereotypes can help us sort through this information with efficiency. The danger, as with all maps, comes when we forget that the territory is more complex than the map. People constitute far more territory than a stereotype can possibly represent.

我们可以把刻板印象想象成地图。有时它们很有用——我们每天都要处理大量信息,而像刻板印象这样的简化信息块可以帮助我们高效地筛选信息。但就像所有地图一样,危险在于我们忘记了实际的疆域远比地图复杂得多。人所构成的疆域远远超出了任何刻板印象所能涵盖的范围。

In the early 1900s, Europeans were snapping pictures all over Palestine, leaving a record that may have reflected their ethnographic perspective but did not cover Karimeh Abbud’s perception of her culture. She began to take photos of those around her, becoming the first Arab woman to set up her own photo studio in Palestine. Her pictures reflected a different take on the territory—she rejected the European style and aimed to capture the middle class of Palestine as they were. She tried to let her camera record the territory as she saw it, rather than manipulating the images to follow a narrative.

20世纪初,欧洲人在巴勒斯坦各地拍摄照片,留下的记录或许反映了他们的民族志视角,但却无法涵盖卡里梅·阿布德对自身文化的感知。她开始拍摄身边的人,成为巴勒斯坦第一位开设个人照相馆的阿拉伯女性。她的照片展现了对这片土地的另一种解读——她摒弃了欧洲式的风格,力求真实地捕捉巴勒斯坦中产阶级的生活。她试图让相机记录她眼中的这片土地,而不是为了迎合某种叙事而对影像进行加工。

Abbud’s informal style and desire to photograph the variety around her, from landscapes to intimate portraits, have left a legacy far beyond the photos themselves. [7] , [8] She contributed a different perspective, a new map, with which to explore the history of the territory of Palestine.

阿布德的非正式风格和拍摄她周围各种事物的愿望,从风景到亲密的肖像,留下了远远超出照片本身的遗产。[7],[8] 她贡献了一种不同的视角,一张新的地图,用以探索巴勒斯坦领土的历史。

We do have to remember, though, that a map captures a territory at a moment in time. Just because it might have done a good job at depicting what was at the time it was made, there is no guarantee that it depicts what is there now or what will be there in the future. The faster the rate of change in the territory, the harder it will be for a map to keep up-to-date.

不过,我们必须记住,地图只能反映某一特定时期的区域状况。即便它在绘制之时能够很好地描绘出当时的景象,也无法保证它能反映出现在或未来的景象。区域变化越快,地图就越难保持更新。

Viewed in its development through time, the map details the changing thought of the human race, and few works seem to be such an excellent indicator of culture and civilization.

—Norman J. W. Thrower [9]

从历史发展的角度来看,这幅地图详细展现了人类思想的变迁,很少有作品能像它一样如此出色地展现文化和文明。——诺曼·J·W·索罗尔[9]

Consider the cartographer: Maps are not purely objective creations. They reflect the values, standards, and limitations of their creators.

想想制图师:地图并非完全客观的创作。它们反映了制图者的价值观、标准和局限性。

One way to see how maps lack objectivity is in the changing national boundaries that make up our world maps. Countries come and go depending on shifting political and cultural sensibilities. When we look at the world map we have today, we tend to associate societies with nations, assuming that the borders reflect a common identity shared by everyone contained within them. However, as historian Margaret MacMillan pointed out, nationalism is a very modern construct, and in some sense has developed with, not in advance of, the maps that set out the shapes of countries. [10] We should not, then, assume that our maps depict an objective view of the geographical territory. For example, historians have shown that the modern borders of Syria, Jordan, and Iraq reflect British and French determination to maintain influence in the Middle East after World War I. [11] Thus, they are a better map of Western interest than of local custom and organization.

地图缺乏客观性的一个方面体现在构成我们世界地图的不断变化的国界线上。国家的兴衰更替取决于政治和文化观念的变迁。当我们审视当今的世界地图时,往往会将社会与国家联系起来,并假定国界反映了其内部所有居民共享的共同身份。然而,正如历史学家玛格丽特·麦克米伦所指出的,民族主义是一个非常现代的概念,在某种意义上,它是伴随着而非先于描绘国家版图的地图而发展起来的。[10] 因此,我们不应假定地图能够客观地反映地理区域。例如,历史学家已经证明,叙利亚、约旦和伊拉克的现代边界反映了英国和法国在一战后维持其在中东影响力的决心。[11] 因此,这些地图更多地反映了西方的利益,而非当地的习俗和组织。

Models are most useful when we consider them in the context in which they were created. What was the cartographer trying to achieve? How does this influence what is depicted in the map?

只有将模型置于其创建的背景下进行考察,才能最大程度地发挥其作用。制图者试图达到什么目的?这如何影响地图上的内容?

Maps can influence territories: This problem was part of the central argument put forth by Jane Jacobs in her groundbreaking work The Death and Life of Great American Cities . Jacobs chronicled the efforts of city planners who came up with elaborate models for the design and organization of cities, without paying any attention to how cities actually work. They then tried to fit the cities into the model. She describes how cities were changed to correspond to these models, and the often negative consequences of these efforts. “It became possible also to map out master plans for the statistical city, and people take these more seriously, for we are all accustomed to believe that maps and reality are not necessarily related, or that if they are not, we can make them so by altering reality.” [12]

地图可以影响地域:这个问题是简·雅各布斯在其开创性著作《美国大城市的死与生》中提出的核心论点之一。雅各布斯记录了城市规划者们如何设计出复杂的城市规划模型,却完全忽视了城市的实际运作方式。他们试图将城市套入这些模型中。她描述了城市如何被改造以符合这些模型,以及这些努力常常带来的负面后果。“人们也开始绘制统计意义上的城市总体规划图,并且更加认真地对待这些规划,因为我们都习惯于认为地图与现实并不一定相关,或者即使它们不相关,我们也可以通过改变现实来使它们相关。”[12]

Jacob’s book is, in part, a cautionary tale about what can happen when faith in the model influences the decisions we make in the territory—when we try to fit complexity into the simplification.

雅各布的书在某种程度上是一个警示故事,讲述了当我们对模型的信仰影响到我们在实际领域中做出的决定时会发生什么——当我们试图将复杂性融入简化之中时会发生什么。

In general, when building statistical models, we must not forget that the aim is to understand something about the real world. Or predict, choose an action, make a decision, summarize evidence, and so on, but always about the real world, not an abstract mathematical world: our models are not the reality.

—David Hand [13]

一般来说,在构建统计模型时,我们不能忘记,我们的目标是理解现实世界。无论是预测、选择行动、做出决策、总结证据等等,都是为了理解现实世界,而不是抽象的数学世界:我们的模型并非现实本身。——大卫·汉德[13]

Conclusion

结论

The map is not the territory is a reminder that our mental models of the world are not the same as the world itself. It’s a caution against confusing our abstractions and representations with the complex, ever-shifting reality they aim to describe.

“地图并非疆域”这句话提醒我们,我们对世界的认知模型与世界本身并不相同。它告诫我们不要将抽象概念和表象与它们试图描述的复杂多变的现实混淆起来。

Mistaking the maps for the territory is dangerous. Consider the person who has a great résumé and checks all the boxes on paper but can’t do the actual job. Updating our maps is a difficult process of reconciling what we want to be true with what is true.

把地图误认为实际地域是危险的。想想那些简历漂亮、纸面上各项条件都符合要求,但却无法胜任实际工作的人。更新我们的认知地图是一个艰难的过程,需要我们调和理想与现实。

In many areas of life, we are offered maps by other people. We are reliant on the maps provided by experts, pundits, and teachers. In these cases, the best we can do is to choose our mapmakers wisely, to seek out those who are rigorous, transparent, and open to revision.

在生活的许多领域,我们都需要借助他人提供的“地图”。我们依赖专家、评论家和教师提供的“地图”。在这种情况下,我们能做的最好的事情就是明智地选择“地图绘制者”,寻找那些严谨、透明且乐于修正的人。

Ultimately, the map/territory distinction is an invitation to engage with the world as it is, not just as we imagine it to be. And remember, when you don’t make the map yourself, choose your cartographer wisely.

归根结底,地图与领土的区别在于,它邀请我们去了解真实的世界,而不仅仅是我们想象中的世界。记住,当你自己不绘制地图时,一定要慎重选择制图师。

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Circle of Competence

能力圈

What don’t you know?

你还有什么不知道的?

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I’m no genius. I’m smart in spots—but I stay around those spots.

—Thomas J. Watson [1]

我不是天才。我在某些方面很聪明——但我只会在这些方面停留。——托马斯·J·沃森[1]
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Understanding where you have an edge in competence and where you don’t helps you prevent problems, spot opportunities, and learn. We all have a circle of competence—an area in which we have a lot of knowledge. The size of that circle is not as important as knowing when you are approaching its perimeter.

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了解自身在哪些方面具备优势,哪些方面存在不足,有助于预防问题、发现机遇并不断学习。我们每个人都有一个能力圈——一个我们拥有丰富知识的领域。这个能力圈的大小并不重要,重要的是了解自己何时接近它的边缘。

Within your circle of competence, you operate with a clear advantage. As you approach the perimeter (the limitations of your knowledge), your advantage starts to decrease. As you cross the perimeter, not only does your advantage vanish, it goes negative. Suddenly, you find yourself playing in an area where others have an advantage.

在你的能力圈内,你拥有明显的优势。当你接近能力圈的边界(即你的知识局限)时,你的优势开始减弱。当你越过能力圈的边界时,你的优势不仅会消失,甚至会变成负值。突然间,你会发现自己身处一个其他人拥有优势的领域。

To get the most out of this mental model, we will explore the following:

为了充分利用这种思维模型,我们将探讨以下内容:

  1. What is a circle of competence?

    什么是能力圈?

  2. How do you know when you have one?

    你怎么知道自己是否患有这种疾病?

  3. How do you build and maintain one?

    如何建造和维护一个?

  4. How do you operate outside of one?

    你如何在体制外运作?

What is a circle of competence? Imagine an old man who’s spent his entire life in a small town. He’s the Lifer. No detail of the goings-on in the town has escaped his notice over the years. He knows the lineage, behaviors, attitudes, job, income, and social status of every person in town. Bit by bit, he has built up that knowledge over a long period of observation and participation in town affairs.

什么是能力圈?想象一下,一位老人一生都生活在一个小镇上。他是这里的“老居民”。多年来,镇上发生的每一件事他都了如指掌。他了解镇上每个人的出身、行为、态度、职业、收入和社会地位。这些知识是他长期观察和参与镇上事务后一点一滴积累起来的。

The Lifer knows all the secrets. He knows where the bodies are buried and who buried them. He knows who owes money to whom, who gets along with whom, and whom the town depends on to keep moving forward. He knows about that time the mayor cheated on his taxes. He knows about the time the town flooded—how many inches high the water was, and exactly who helped whom and who didn’t.

终身监禁犯知道所有的秘密。他知道尸体埋在哪里,是谁埋的。他知道谁欠谁的钱,谁和谁关系好,以及小镇的运转依赖于谁。他知道市长偷税漏税的事。他知道小镇被淹的那次——水位有多高,以及究竟是谁帮助了谁,谁袖手旁观。

Now imagine a stranger enters the town, in from the Big City. Within a few days, the Stranger decides that he knows all there is to know about the town. He’s met the mayor, the sheriff, the bartender, and the shopkeeper, and he can get around fairly easy. It’s a small town, and he hasn’t come across anything surprising.

现在想象一下,一个陌生人从大城市来到这座小镇。几天之内,这个陌生人就觉得自己对小镇了如指掌。他认识了镇长、警长、酒保和店主,而且出行也很方便。这是一个小镇,他也没遇到什么令人惊讶的事情。

In the Stranger’s mind, he’s convinced he knows pretty much everything a Lifer would know; with his keen eye, he has sized up the town in no time. He makes assumptions based on what he has learned so far and figures he knows enough to get his business done. This belief, however, stems from a false sense of confidence that likely causes him to take more risks than he realizes. Without intimately knowing the history of the town, how can he be sure that he has picked the right land for development or negotiated the best price?

在陌生人看来,他确信自己对这座小镇了如指掌,就像一个老居民一样;凭借敏锐的眼光,他很快就摸清了全镇的情况。他根据目前所了解的信息做出假设,认为自己掌握的信息足以完成交易。然而,这种想法源于一种虚假的自信,很可能让他承担了比自己意识到的更大的风险。如果对小镇的历史一无所知,他又如何能确定自己选对了开发用地,或者谈妥了最优惠的价格呢?

After all, what kind of knowledge does he really have, compared to the Lifer?

毕竟,与终身监禁犯相比,他究竟掌握了多少知识?

The difference between the detailed web of knowledge in the Lifer’s head and the surface knowledge in the Stranger’s head is the difference between being inside a circle of competence and being outside its perimeter. True knowledge of a complex territory cannot be faked. When it comes to this town, the Lifer could stump the Stranger in no time, but not the other way around. Consequently, as long as the Lifer is operating in his circle of competence, he will always have a better understanding of reality to use in making decisions. Having this deep knowledge gives him flexibility in responding to challenges, because he will likely have more than one solution to every problem. This depth also increases his efficiency—he can eliminate bad choices quickly because he has all the pieces of the puzzle.

资深居民头脑中错综复杂的知识网络与陌生人头脑中肤浅的知识之间的区别,就好比身处能力圈内与身处能力圈外的区别。对复杂领域的真正了解是无法伪造的。就这座小镇而言,资深居民可以很快难倒陌生人,反之则不然。因此,只要资深居民在其能力圈内活动,他就能始终对现实有更深刻的理解,从而做出更明智的决策。这种深厚的知识使他能够灵活应对挑战,因为他很可能对每个问题都有不止一个解决方案。这种深度也提高了他的效率——他可以迅速排除错误的选择,因为他掌握了所有关键信息。

What happens when you take the Lifer/Stranger idea seriously and try to delineate carefully the domains in which you’re one or the other? There is no definitive checklist for figuring this out, but if you don’t have at least a few years and a few failures under your belt, you cannot consider yourself competent in a circle.

当你认真对待“终身玩家/陌生人”这个概念,并试图仔细界定你在哪些领域属于其中之一时,会发生什么?虽然没有明确的清单可以帮助你弄清楚这一点,但如果你没有至少几年的经验和一些失败的教训,你就不能认为自己在某个圈子里称职。

We shall be unable to turn natural advantage to account unless we make use of local guides.

—Sun Tzu [2]

如果我们不借助当地向导,就无法利用自然优势。——孙子[2]

For most of us, climbing to the summit of Mount Everest is outside our circle of competence. Not only do we have no real idea how to do it, but—even more scary—should we attempt it, we don’t even know what we don’t know. If we studied hard, maybe we’d figure out the basics. We’d learn about the training, the gear, the process, the ideal time of year to climb, all the things an outsider could quickly come to know. But at what point would you be satisfied that you knew enough to get up there, and back, with your life intact? And how confident would you be in this assessment?

对我们大多数人来说,攀登珠穆朗玛峰超出了我们的能力范围。我们不仅不知道该如何攀登,更可怕的是,如果我们真的尝试了,我们甚至不知道自己不知道什么。如果我们努力学习,或许能掌握一些基本知识。我们会了解训练、装备、流程、最佳攀登时间等等,这些都是外行人可以很快了解的。但是,你究竟要掌握多少知识才能确信自己已经足够安全登顶并返回?你对这种评估又有多大的信心呢?

There are approximately two hundred bodies on Mount Everest (to say nothing of the ones that have been removed). None of those people thought Everest would take their life. The climate preserves their corpses, almost as a warning. The ascent to the summit takes you past the bodies of people who once shared your dreams.

珠穆朗玛峰上大约有两百具遗体(还不包括已被移出的)。这些人谁也没想到珠峰会夺走他们的生命。严酷的气候保存了他们的遗体,仿佛是一种警示。攀登珠峰的途中,你会经过那些曾经与你共享梦想的人们的遗骸。

Since the first recorded attempts to climb Mount Everest, in 1922, all climbers have relied on the specialized knowledge of the Sherpa people to help navigate the terrain of the mountain. Indigenous to the region, Sherpas grew up in the shadow of the mountain, making them uniquely placed to develop the expertise necessary to get to the top.

自1922年首次有记录的攀登珠穆朗玛峰以来,所有登山者都依赖夏尔巴人的专业知识来帮助他们应对山上的地形。夏尔巴人是该地区的土著居民,在珠峰的庇护下长大,这使他们拥有得天独厚的优势,能够发展出登顶所需的专业技能。

Sherpa Tenzing Norgay led the team that made the first successful ascent, [3] and a quarter of all subsequent ascents have been made by Sherpas (some going as many as sixteen times). [4] , [5] Although the mountain is equally risky for everyone, most people who climb Everest do it only once. For the Sherpas, working and climbing various parts of the mountain is their day job. Would you try to climb Everest without their help?

夏尔巴人丹增·诺尔盖带领的团队完成了首次珠峰登顶[3],此后所有登顶的次数中,有四分之一是由夏尔巴人完成的(有些人甚至登顶多达16次)[4],[5]。虽然珠峰对每个人来说都同样危险,但大多数人只攀登过一次。对于夏尔巴人来说,在珠峰上工作和攀登是他们的日常工作。如果没有他们的帮助,你会尝试攀登珠峰吗?

The physical challenges alone of reaching the summit are staggering. It is a climate that humans aren’t suited for. There isn’t enough oxygen in the air, and the top of the mountain is regularly pummeled by winds of more than 150 miles an hour—stronger than a Category 5 hurricane. You don’t get to the top on a whim, and you don’t survive with only luck. Norgay worked for years as a trekking porter and was part of a team that tried to ascend Everest in 1935. He finally succeeded in reaching the summit in 1953, after twenty years of climbing and trekking in the region. He developed his expertise through lots of lucky failures. After summitting Everest, Norgay opened a mountaineering school, to train other locals as guides, and a trekking company, to take others climbing in the Himalayas.

单是登顶珠峰的体能挑战就令人叹为观止。那里的气候并不适合人类生存。空气中氧气稀薄,山顶经常遭受时速超过150英里(约240公里)的狂风袭击——比五级飓风还要猛烈。登顶绝非一时兴起,也并非仅凭运气就能成功。诺尔盖曾多年担任登山背夫,并参与了1935年攀登珠峰的尝试。经过二十年的登山和徒步旅行,他终于在1953年成功登顶。他从无数次侥幸失败的经历中积累了丰富的经验。登顶珠峰后,诺尔盖创办了一所登山学校,培训当地人成为向导,并成立了一家徒步旅行公司,带领游客前往喜马拉雅山脉登山。

When it comes to the competence required to climb Mount Everest, Norgay is around the closest someone could come to being a Lifer.

论攀登珠穆朗玛峰所需的技能,诺尔盖可以说是最接近“终身登山者”的人了。

I never allow myself to have an opinion on anything that I don’t know the other side’s argument better than they do.

—Charlie Munger [6]

我从不对任何我不了解对方论点的事情发表意见。——查理·芒格[6]

How Do You Know When You Have a Circle of Competence?

如何判断你是否拥有了能力圈?

Within our circles of competence, we know what we don’t know. We can make decisions quickly and relatively accurately. We can accurately define the problem. We possess detailed knowledge of additional information we might need to make a decision. We have a proven track record. We can seamlessly adapt our language to a different level, zooming in or out. We know what is knowable.

在我们的能力范围内,我们清楚自己的知识盲区。我们能够快速且相对准确地做出决策。我们能够准确地定义问题。我们掌握决策所需的其他详细信息。我们拥有良好的过往业绩。我们能够灵活地调整语言表达方式,根据情况放大或缩小。我们知道什么是可知的。

Within our circle of competence, we can anticipate and respond to counterarguments, because we understand them better than the person making them. We also have a lot of options when we confront problems in our circles of competence. Our deep fluency in the subjects we are dealing with means we can draw on different information resources and understand what can be adjusted and what is invariant.

在我们的能力圈内,我们能够预见并应对反驳论点,因为我们比提出反驳论点的人更了解它们。当我们在能力圈内遇到问题时,我们也有很多选择。我们对所处理领域的深入了解意味着我们可以利用不同的信息资源,并理解哪些可以调整,哪些是不变的。

A circle of competence cannot be built quickly. We don’t become Lifers overnight, or as the result of taking a few courses or working at something for a few months—being a Lifer requires more than skimming the surface. In Alexander Pope’s poem “An Essay on Criticism,” he writes:

能力圈无法速成。我们不可能一夜之间成为终身专家,也不是上了几个课程或工作几个月就能做到的——成为终身专家需要的远不止是浅尝辄止。亚历山大·蒲柏在他的诗作《论批评》中写道:

A little learning is a dangerous thing;

Drink deep, or taste not the Pierian spring:

There shallow draughts intoxicate the brain,

And drinking largely sobers us again. [7]

浅尝辄止是危险的;要么畅饮,要么就别尝皮埃里亚泉水的滋味:浅尝辄止会使大脑陶醉,而畅饮则会使人清醒。[7]

There is no shortcut to understanding. Building a circle of competence takes years of experience, of making mistakes, and of actively seeking out better methods of practice and thought.

理解没有捷径。构建能力圈需要多年的经验积累,需要不断从错误中吸取教训,并积极寻求更好的实践和思考方法。

How Do You Build and Maintain a Circle of Competence

如何构建和维护能力圈?

One of the essential requirements of a circle of competence is that you can never take it for granted. The terrain is always shifting. You can’t operate as if a circle of competence is a static thing that, once attained, is attained for life. The world is dynamic. Knowledge gets updated, and so too must your circle.

能力圈的基本要求之一就是永远不能想当然。形势瞬息万变。你不能把能力圈当作一成不变的东西,认为一旦建立就终身有效。世界是动态的,知识会更新,你的能力圈也必须随之更新。

There are three key practices needed to build and maintain a circle of competence: curiosity and a desire to learn, monitoring, and feedback.

建立和维护能力圈需要三种关键实践:好奇心和学习的愿望、监控和反馈。

First, you have to be willing to learn. Learning comes when experience pairs with reflection. Experiences can be yours or those of others, absorbed through books, articles, and conversations. Learning everything on your own is costly and slow. You are one person. Learning from the experiences of others is much more productive. The key to learning is reflecting on those experiences and compressing them into something usable. You need to approach your circle of competence with curiosity, seeking out information that can help you expand and strengthen it.

首先,你必须愿意学习。学习源于经验与反思的结合。经验可以是你自己的,也可以是他人的,可以通过书籍、文章和对话等途径吸收。独自学习一切既费时又费力。毕竟,你只有一个人。借鉴他人的经验会更加高效。学习的关键在于反思这些经验,并将它们提炼成可用的知识。你需要以好奇心探索你的能力圈,寻找能够帮助你拓展和强化自身能力的信息。

I want to think about things where I have an advantage over other people. I don’t want to play a game where people have an advantage over me…. I don’t play in a game where other people are wise and I am stupid. I look for a game where I am wise and they are stupid. And believe me, it works better.

—Charlie Munger [8]

我想思考那些我比别人有优势的事情。我不想玩那种别人比我强的游戏……我不玩那种别人聪明而我愚蠢的游戏。我寻找的是我聪明而他们愚蠢的游戏。相信我,这样效果更好。——查理·芒格[8]

Second, you need to monitor your track record in areas in which you have, or want to have, a circle of competence. And you need to have the courage to monitor honestly , so the feedback you receive can be used to your advantage.

其次,你需要密切关注你在自己已经具备或希望建立能力圈的领域中的表现记录。而且,你需要有勇气诚实地审视这些记录,这样才能利用收到的反馈来提升自己。

The reason we have such difficulty with overconfidence—as demonstrated in studies that show that most of us are much worse drivers, lovers, managers, traders (and many other things) than we think we are—is because we have a problem with honest self-assessment. We don’t keep the right records, because we don’t really want to know what we’re good and bad at. Ego is a powerful enemy when it comes to better understanding reality.

我们之所以如此难以克服过度自信——研究表明,我们大多数人的驾驶、恋爱、管理、交易能力(以及许多其他方面)都远不如自己想象的那样出色——原因在于我们缺乏诚实的自我评估能力。我们不去认真记录自己的表现,因为我们并不真正想知道自己的长处和短处。在更好地了解现实的过程中,自负是一个强大的敌人。

But protecting your ego won’t work if you’re trying to assess or build your circle of competence. You need to keep a precise diary of your thinking. If you’re an investor, this might be information about your trades in the stock market. If you are in a leadership position, you need to observe and chronicle the results of your decisions and evaluate the outcomes based on what you set out to achieve. You need to be honest about your failures in order to reflect on and learn from them. That’s what it takes.

但如果你想评估或拓展自己的能力圈,维护自尊心是行不通的。你需要详细记录你的思考过程。如果你是投资者,这可能包括你在股市的交易信息。如果你身居领导职位,你需要观察并记录决策的结果,并根据你设定的目标评估结果。你需要坦诚面对失败,才能反思并从中吸取教训。这才是成功之道。

You need to make the invisible thoughts in your head visible. Keeping a journal of your own performance is the easiest and most private way to give self-feedback. Journals allow you to step out of your automatic thinking and ask yourself: What went wrong? How could I do better? Monitoring your own performance allows you to see patterns that you simply couldn’t see before. This type of analysis is painful for the ego, which is also why it helps build a circle of competence. You can’t improve if you don’t know what you’re doing wrong.

你需要将脑海中那些无形的想法具象化。记录自己的表现是最简单、最私密的自我反馈方式。日记能让你跳出自动思维的束缚,扪心自问:哪里出了问题?我该如何做得更好?监控自己的表现能让你发现之前根本无法察觉的模式。这种分析对自尊心来说或许有些痛苦,但也正因如此,它有助于构建能力圈。如果你不知道自己错在哪里,就无法进步。

Finally, you must occasionally solicit other perspectives. This helps build a circle of competence but is also critical for maintaining one.

最后,你必须时不时地征求其他人的意见。这有助于构建能力圈,而且对于维护能力圈也至关重要。

A lot of professionals have an ego problem: their view of themselves does not line up with the way other people see them. Before people can change, they need to be familiar with these outside perspectives. We need to go to people we trust, who can give us honest feedback about our traits. These people are in a position to observe us operating within our circles, and are thus able to offer relevant perspectives on our competence. Another option is to hire a coach.

很多职场人士都存在自负问题:他们对自己的认知与他人对他们的看法并不一致。在改变之前,人们需要熟悉这些外部视角。我们需要向信任的人寻求帮助,让他们就我们的特质给出诚实的反馈。这些人能够观察我们在各自圈子中的表现,因此能够对我们的能力提供相关的见解。另一种选择是聘请一位教练。

Atul Gawande is one of the top surgeons in the United States. When he wanted to get better at being a surgeon, he hired a coach. This is terribly difficult for anyone to do, let alone a doctor. At first, Gawande felt embarrassed. It had been over a decade since he was evaluated by another person, in medical school. “Why,” he asked, “should I expose myself to the scrutiny and fault-finding?” [9]

阿图尔·加万德是美国顶尖的外科医生之一。为了提升自己的外科医术,他聘请了一位教练。这对任何人来说都是极其困难的,更何况是一位医生。起初,加万德感到很尴尬。自从十多年前在医学院接受他人评估以来,他再也没有接受过评估。“我为什么要,”他问道,“让自己暴露在审视和挑剔之下呢?”[9]

The coaching worked. Gawande later wrote that he got two things out of this experience. First, he received information about something he couldn’t see himself and that no one else would point out (if they noticed it at all): knowledge of where his skill and technique were suboptimal. The second thing he gained was the ability to provide better feedback to other doctors.

这次指导奏效了。加万德后来写道,他从这段经历中收获了两点。首先,他获得了自己看不到、别人也不会指出(即便注意到)的信息:他意识到自己的技能和技巧在哪些方面不够完善。其次,他获得了为其他医生提供更有效反馈的能力。

It is extremely difficult to maintain a circle of competence without an outside perspective. We usually have too many biases to rely solely on our own observations. It takes courage to solicit external feedback, so if you notice yourself start to manifest defensiveness, focus instead on the result you hope to achieve.

如果没有外部视角,就很难维持一个能力圈。我们通常会受到太多偏见的影响,无法仅仅依靠自己的观察。寻求外部反馈需要勇气,所以如果你发现自己开始表现出防御心理,那就把注意力集中在你希望达成的结果上。

How Do You Operate Outside a Circle of Competence?

如何在能力圈之外开展工作?

Part of the advantage to understanding your circle of competence is understanding when you are approaching, or arrive on the other side of, its perimeter.

了解自己的能力圈的好处之一是,了解自己何时接近或到达能力圈的边缘。

Since we can’t be inside a circle of competence in everything, when we find ourselves Strangers in a place filled with Lifers, what do we do? We don’t always get to “stay around our spots.” We must develop a repertoire of techniques for managing when we’re outside of our sphere, which happens all the time. [10]

既然我们不可能在所有方面都处于自己的能力圈内,那么当我们发现自己身处一个全是老手的地方时,我们该怎么办?我们不可能总是“待在自己的位置上”。我们必须发展出一套应对身处自己能力圈之外情况的技巧,而这种情况总是会发生。[10]

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There are three practices necessary to successfully operating outside a circle of competence:

要想在自身能力范围之外成功开展工作,需要具备以下三种实践经验:

  1. Learn the basics of the realm you’re operating in, while still acknowledging that you’re a Stranger, not a Lifer. Keep in mind that basic information is easy to obtain and tends to seduce the acquirer into possessing unwarranted confidence.

    了解你所处领域的方方面面,同时也要明白你只是个外来者,而非老手。记住,基本信息很容易获取,也容易让人产生不必要的自信。

  2. Talk to someone whose circle of competence in the area is strong. Take the time to do a bit of research, to define questions you need to ask and information you need to obtain to make a good decision. If you ask an expert what to do, they will give you an answer, but you won’t have learned anything. If you ask them what variables matter in this situation and why, you’ll learn not only what they would do but why they would do it. Furthermore, when you need the advice of others, especially in higher-stakes situations, ask questions to probe the limits of their circles of competence. Then, ask yourself how the situation might influence the information they choose to provide to you (always remember: consider the cartographer).

    与在该领域拥有丰富经验的人交流。花些时间做一些调查研究,明确你需要提出的问题以及需要获取的信息,以便做出明智的决定。如果你直接问专家该怎么做,他们会给你答案,但你却什么也学不到。如果你问他们在这种情况下哪些变量比较重要,以及为什么,你不仅会知道他们会怎么做,还会知道他们为什么这么做。此外,当你需要他人的建议时,尤其是在风险较高的情况下,要提出问题来探究他们的能力范围。然后,问问自己,这种情况可能会如何影响他们选择提供的信息(永远记住:要考虑地图绘制者)。

  3. Use a broad understanding of the basic mental models of the world to augment your limited understanding of the field in which you find yourself a Stranger. These will help you identify the foundational concepts that would be most useful, which will then serve as a guide to help you navigate the situation you are in.

    运用对世界基本心智模型的广泛理解,来弥补你对身处陌生领域的认知不足。这将帮助你识别出最有用的基础概念,这些概念将指导你应对当前的情况。

There are inevitably areas where you are going to be a Stranger, even in the profession in which you excel. It is impossible for our circles of competence to encompass the entire world. Even if we’re careful to know the boundaries of our circles and take them seriously, we can’t always operate inside our circles. Life is simply not that forgiving. We have to make HR decisions without being experts in human psychology, implement technology without having the faintest idea how to fix it if something goes wrong, or design products with an imperfect understanding of our customers. These decisions may be outside our circles, but they still have to get made.

即使在你擅长的领域,也难免会遇到你感到陌生的领域。我们的能力圈不可能涵盖整个世界。即使我们谨慎地了解并认真对待自身能力圈的边界,也无法始终在圈内运作。生活并非如此宽容。我们可能需要在不精通人性心理学的情况下做出人力资源决策,在对技术故障的修复一无所知的情况下实施技术,或者在对客户了解不足的情况下设计产品。这些决策或许超出了我们的能力圈,但它们仍然需要被做出。

When Queen Elizabeth I of England ascended to the throne, the security of her reign was by no means assured. The tumultuous years under her father, brother, and sister had contributed to a political situation that was precarious at best. England was in a religious crisis that was threatening the stability of the kingdom, and the nation was essentially broke.

当英国女王伊丽莎白一世登基时,她的统治远非稳固。在她父亲、哥哥和姐姐统治时期动荡不安的岁月,使得当时的政治局势岌岌可危。英国正处于宗教危机之中,这场危机威胁着王国的稳定,而国家也实际上已经破产。

Elizabeth knew there were aspects of leading the country that were outside her circle of competence. She had an excellent education and had spent most of her life just trying to survive. Perhaps that is why she was so able to identify and admit to what she didn’t know.

伊丽莎白深知,治理国家有些方面超出了她的能力范围。她受过良好的教育,一生中大部分时间都只是为了生存而挣扎。或许正因如此,她才能如此清晰地认识到自己的不足并坦然承认。

In her first speech as queen, Elizabeth announced, “I mean to direct all my actions by good advice and counsel.” [11] After outlining her intent upon becoming queen, she proceeded to build her Privy Council—effectively the royal advisory board. She didn’t copy her immediate predecessors by filling her council with yes-men or wealthy incompetents who happened to share her religious values. To develop stability and achieve continuity, she blended the old and the new. She kept the group small, so that real discussions could happen. She wanted a variety of opinions that could be challenged and debated. [12]

伊丽莎白女王在就任后的首次演讲中宣布:“我将以良言良策指导我的一切行动。”[11] 在阐明其登基意图后,她着手组建枢密院——实际上是皇家顾问委员会。她没有像其前任那样,任由唯唯诺诺之辈或恰巧与她宗教信仰相同的有钱无能之辈充斥其委员会。为了建立稳定和保持延续性,她将新旧元素融合在一起。她将委员会规模控制在较小范围内,以便进行真正的讨论。她希望听到各种不同的观点,并接受挑战和辩论。[12]

In large measure due to the advice she received from this council—advice that was the product of open debate that took in the circles of competence of each of the participants—Elizabeth took England from a country of civil unrest and frequent persecution to one that inspired loyalty and creativity in its citizens. She sowed the seeds for the empire that would eventually come to control one-quarter of the globe.

伊丽莎白一世之所以能取得今天的成就,很大程度上要归功于她从这个委员会获得的建议——这些建议源于公开辩论,涵盖了每位参与者各自的专业领域——她将英国从一个内乱频仍、饱受迫害的国家,转变为一个激发公民忠诚和创造力的国家。她播下了帝国的种子,这个帝国最终将控制全球四分之一的领土。

Conclusion

结论

The first rule of competition is, you are more likely to win if you play where you have an advantage. Doing so requires a firm understanding of what you know and what you don’t know. Your circle of competence is your personal sphere of expertise, the area where your knowledge and skills are concentrated. It’s the domain where you have a deep understanding, where your judgments are reliable, and your decisions are sound.

竞争的第一法则就是:在自己拥有优势的领域竞争,获胜的几率更大。而做到这一点,需要你对自己已知和未知的领域有清晰的认识。你的能力圈就是你的个人专长领域,是你知识和技能集中的领域。在这个领域,你拥有深刻的理解,你的判断可靠,你的决策也稳健合理。

The size of your circle isn’t as important as knowing the boundaries. The wise person is the one who knows the limits of their knowledge, who can say with confidence, “This falls within my circle,” or “This is outside my area of expertise.”

你的社交圈大小并不重要,重要的是了解它的边界。智者懂得自身知识的局限,能够自信地说:“这在我的认知范围内”,或者“这超出了我的专业领域”。

Operating within your circle of competence is a recipe for confidence and effectiveness. But venturing outside your circle of competence is a recipe for trouble. You’re like a sailor navigating unfamiliar waters without a map, at the mercy of currents and storms you don’t fully understand. This isn’t to say that you should never venture outside your circle. Learning new things, gaining new skills, mastering new domains is one of the beautiful things about life.

在自身能力范围内行事,是建立自信和提高效率的秘诀。但冒险涉足能力范围之外,则会带来诸多麻烦。你就像一个没有地图就航行在陌生水域的水手,只能任由你并不完全了解的暗流和风暴摆布。但这并不是说你永远不应该冒险。学习新事物、掌握新技能、精通新领域,正是人生的一大乐趣。

Celebrate your expertise, but also acknowledge your limitations.

展现你的专长,但也要正视你的局限性。

Ignorance more often begets confidence than knowledge.

—Charles Darwin [13]

无知比知识更容易滋生自信。——查尔斯·达尔文[13]
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Supporting Idea:
Falsifiability

支持性观点:可证伪性

Karl Popper wrote, “A theory is part of empirical science if and only if it conflicts with possible experiences and is therefore in principle falsifiable by experience.” [15] The idea here is that if you can’t prove something wrong, you can’t really prove it right either.

卡尔·波普尔写道:“一个理论是经验科学的一部分,当且仅当它与可能的经验相冲突,因此原则上可以通过经验证伪。”[15] 这里的想法是,如果你不能证明某件事是错的,你也不能真正证明它是正确的。

Thus, in Popper’s words, science requires testability: “If observation shows that the predicted effect is definitely absent, then the theory is simply refuted.” [16] A good theory must have an element of risk to it—namely, it has to risk being wrong. It must be able to be proven wrong under stated conditions.

因此,用波普尔的话来说,科学需要可检验性:“如果观察表明预测的效应确实不存在,那么该理论就被驳斥了。”[16] 一个好的理论必须包含一定的风险因素——也就是说,它必须有出错的风险。它必须能够在既定条件下被证明是错误的。

In a true science, as opposed to a pseudoscience, the following statement can be easily made: “If x happened, it would show demonstrably that theory y is not true.” We can then design an experiment—a physical one, or sometimes a thought experiment—to figure out if x actually does happen . Falsification is the opposite of verification: you must try to show that the theory is incorrect and, if you fail to do so, you actually strengthen it. To understand how this works in practice, think of evolution. As mutations appear, natural selection eliminates those that don’t work, thereby strengthening the fitness of the rest of the population.

在真正的科学(而非伪科学)中,我们可以很容易地得出这样的结论:“如果x发生,就能确凿地证明理论y是错误的。” 然后,我们可以设计一个实验——可以是物理实验,有时也可以是思想实验——来验证x是否真的发生。证伪与验证相反:你必须努力证明理论是错误的,如果你失败了,实际上就加强了它。为了理解这在实践中是如何运作的,可以想想进化论。随着突变的出现,自然选择会淘汰那些不适应环境的突变体,从而增强其余个体的适应性。

Consider Popper’s discussion of the concept of falsifiability in the context of Freud’s psychoanalytic theory, which is broadly about repressed childhood memories influencing our unconscious, which in turn affects our behavior. Popper was careful to say that it is not possible to prove that Freudianism is either true or not true, at least in part. We can simply say that we don’t know whether it’s true, because it does not make specific, testable predictions. It may have many kernels of truth in it, but we can’t tell. The theory would have to be restated in a way that would allow for experience to refute it.

不妨思考一下波普尔在弗洛伊德精神分析理论背景下对可证伪性概念的讨论。弗洛伊德的精神分析理论大致认为,被压抑的童年记忆会影响我们的无意识,进而影响我们的行为。波普尔谨慎地指出,我们无法证明弗洛伊德主义的真假,至少无法证明它在某些方面是正确的。我们只能说,我们不知道它是否正确,因为它没有做出具体的、可检验的预测。它或许包含许多真理的内核,但我们无法判断。我们需要以一种能够让经验反驳它的方式来重新表述这个理论。

Another interesting piece of Popper’s work was an attack on what he called “historicism”—the idea that history has fixed laws or trends that inevitably lead to certain outcomes. Historicism includes the tendency to use examples from the past to make definitive conclusions about what is going to happen in the future.

波普尔另一项引人入胜的著作是对他所谓的“历史主义”的批判——历史主义认为历史存在固定的规律或趋势,必然导致某些结果。历史主义包括一种倾向,即利用过去的例子来对未来做出确凿的结论。

Popper considered this kind of thinking pseudoscience—or, worse, a dangerous ideology that tempts wannabe state planners and utopians to control society. He did not consider historicist doctrines falsifiable. There is no way, for example, to test whether there is a “Law of Increasing Technological Complexity” in human society, as many are tempted to claim these days, because it is not actually a testable hypothesis. Instead of calling these ideas interpretations, historicists call them “laws,” or some similarly connotative word that implies an unchanging and universal state that is not open to debate, thereby giving them an authority that they haven’t earned. Too frequently, these postulated “laws” become immune to falsifying evidence—any new evidence is interpreted through the lens of the theory.

波普尔认为这种思维方式是伪科学——或者更糟,是一种危险的意识形态,它诱使那些妄图建立国家的人和乌托邦主义者控制社会。他认为历史主义的教条是不可证伪的。例如,正如许多人如今所声称的那样,人类社会是否存在“技术复杂性递增规律”是无法检验的,因为它实际上并非一个可检验的假设。历史主义者不称这些观点为解释,而是称之为“规律”,或者其他类似的带有暗示性的词语,这些词语暗示着一种不变的、普遍的、不容置疑的状态,从而赋予了它们不应有的权威。这些假定的“规律”常常不受证伪证据的影响——任何新的证据都会被套用该理论的框架来解读。

For example, we can certainly find confirmation for the idea that humans have progressed, in a specifically defined way, toward increasing technological complexity. But is that a “law” of history, in the sense of being inviolable? Was it always going to be this way? No matter what the starting conditions or developments along the way, were humans always going to increase our technological prowess? We really can’t say.

例如,我们当然可以找到证据来证实人类确实以一种特定的方式朝着技术复杂性不断提高的方向发展。但这是否是一条不可违背的历史“法则”?历史是否一直都会如此发展?无论起点如何,无论发展历程如何,人类的技术能力是否注定会不断提升?我们真的无法断言。

Here, we hit on the problem of trying to assert any fundamental law by which human history must inevitably progress. Trend is not destiny. Even if we can derive and understand certain laws of human biological nature, the trends of history itself are dependent on conditions, and conditions change.

这里,我们触及了一个问题:试图断言人类历史必然遵循某种根本规律是行不通的。趋势并非命运。即便我们能够推导出并理解某些人类生物学规律,历史的走向本身也取决于各种条件,而条件总是在变化。

Bertrand Russell’s classic example of the chicken that gets fed every day is a great illustration of this concept. [17] Daily feedings have been going on for as long as the chicken has observed, and thus it supposes that these feedings are a guaranteed part of its life and will continue in perpetuity. The feedings appear as a law—until the day the chicken gets its head chopped off. They are then revealed to be a trend, not a predictor of the future state of affairs.

伯特兰·罗素的经典例子——每天喂食的鸡——很好地阐释了这一概念。[17] 每天喂食的习惯由来已久,因此鸡认为这是它生活中不可或缺的一部分,并将永远持续下去。喂食似乎成了一条规律——直到鸡的头被砍掉的那一天。那时,喂食的规律才显露出来,它只是一种趋势,而非未来状态的预兆。

Another way to look at it is to examine how we tend to view the worst events in history. We tend to assume that the worst that has happened is the worst that can happen, and then prepare for that. We forget that “the worst” once smashed a previous understanding of what was the worst. Therefore, we need to prepare more for the extremes allowable by physics rather than for what has happened until now.

换个角度来看,我们可以审视一下我们看待历史上最糟糕事件的惯常方式。我们往往认为已经发生的最糟糕的情况就是可能发生的最糟糕的情况,然后以此为目标做好准备。我们却忘记了,“最糟糕的情况”曾经颠覆了我们以往对“最糟糕的情况”的认知。因此,我们更需要为物理学允许的极端情况做好准备,而不是仅仅为过去发生的事情做好准备。

Applying the filter of falsifiability helps us sort through which theories are more robust. If a theory can’t ever be proven false, because we have no way of testing it, then the best we can do is try to determine its probability of being true.

运用可证伪性筛选标准可以帮助我们区分哪些理论更稳健。如果一个理论永远无法被证伪,因为我们没有办法检验它,那么我们所能做的最好的就是尝试确定它为真的概率。

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First Principles Thinking

第一性原理思维

Go back to basics.

回归基本。

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I don’t know what’s the matter with people: they don’t learn by understanding; they learn by some other way—by rote or something. Their knowledge is so fragile!

—Richard Feynman [1]

我不明白现在的人是怎么了:他们不通过理解来学习,而是通过其他方式学习——比如死记硬背。他们的知识太脆弱了!——理查德·费曼[1]
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First principles thinking is one of the best ways to discover new solutions. Sometimes called “reasoning from first principles,” it’s a tool to help break down complicated problems by separating what we know is absolutely true from anything that is an assumption. What remain are the essentials. If you know the first principles of something, you can build the rest of your knowledge around them to produce something new.

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第一性原理思维是发现新解决方案的最佳方法之一。它有时也被称为“从第一性原理出发的推理”,是一种帮助我们分解复杂问题的工具,它能将我们已知的绝对真理与任何假设区分开来。剩下的就是本质。如果你掌握了某个事物的第一性原理,你就可以围绕这些原理构建其余的知识,从而创造出新的事物。

While you could take this way of thinking down to an atomic level, a lot of value is gained by simply going a level or two deeper than most people. [2] Solutions are based on what you see. Different answers reveal themselves at different levels.

虽然这种思考方式可以细化到原子层面,但仅仅比大多数人深入一两层就能获得很多价值。[2] 解决方案取决于你的观察。不同的答案会在不同的层面上显现。

If I hand you a house made from Lego blocks, you know it’s possible to make a house. Thinking at the first layer, you might move a few blocks around and, in the process, slightly improve the house. Most people stop here. They are presented with something that already exists and they endeavor to make it slightly better. Going a layer deeper and breaking the Lego house into individual pieces opens the door to possibility: not only can you build a better house, you can build something entirely different.

如果我给你一座用乐高积木搭成的房子,你知道这是可以搭建的房子。乍一看,你可能会移动几块积木,稍微改进一下房子。大多数人到此为止。他们面对的是一个现成的东西,并试图让它变得更好一些。但如果深入思考,把乐高房子拆解成一个个独立的部件,就能开启无限可能:你不仅可以搭建一座更好的房子,还可以搭建一座完全不同的房子。

Everything that exists is effectively a set of Lego blocks, assembled in a certain way, that can be taken apart and reassembled. A bike is just a seat, chain, body, handlebars, etc. Breaking the bike down into its parts allows you to reassume the parts into something new. However, you can also go deeper, melting the parts into their core metals and making a shield, sword, or anything else, limited only by material and imagination.

世间万物本质上都是一套乐高积木,以某种方式组装而成,可以拆卸,也可以重新组装。自行车就是由车座、链条、车身、车把等等组成的。将自行车拆解成各个部件,就能将这些部件重新组合成新的物品。不仅如此,你还可以更进一步,将这些部件熔化成金属芯,打造盾牌、宝剑或其他任何物品,唯一的限制就是材料和想象力。

The idea of building knowledge from first principles has a long tradition in philosophy. In the Western canon it goes back to Plato, with significant contributions from Aristotle and Descartes. Essentially, these thinkers were looking for foundational knowledge that would not change and on which we could build everything else, from our ethical systems to our social structures.

从基本原理构建知识的理念在哲学中由来已久。在西方经典中,这一理念可以追溯到柏拉图,亚里士多德和笛卡尔也做出了重要贡献。本质上,这些思想家都在寻求永恒不变的基础知识,我们可以以此为基础构建一切,从伦理体系到社会结构。

First principles thinking doesn’t have to be quite so grand. When we do it, we aren’t necessarily looking for absolute truths—millennia of epistemological inquiry have shown us that these are hard to come by, and the scientific method has demonstrated that knowledge can be built only when we are actively trying to falsify it (see “Supporting Idea: Falsifiability”). Rather, first principles thinking identifies the elements that are, in the context of any given situation, irreducible.

第一性原理思考不必如此宏大。我们运用第一性原理思考时,并非一定要寻找绝对真理——数千年的认识论探究已经表明,绝对真理难以获得,而科学方法也证明,知识只有在我们积极尝试证伪它时才能构建(参见“支持观点:可证伪性”)。相反,第一性原理思考旨在识别在任何特定情境下不可简化的要素。

First principles do not provide a checklist of things that will always be true; our knowledge of first principles changes as we understand more. They are the foundation on which we must build, and thus will be different in every situation—but the more we know, the more we can challenge. For example, if we are considering how to improve the energy efficiency of a refrigerator, the laws of thermodynamics can be taken as first principles. However, a theoretical chemist or physicist might want to explore entropy, and thus further break the second law of thermodynamics into its underlying principles and the assumptions that were made because of them. First principles are the boundaries that we must work within in any given situation, so when it comes to thermodynamics, an appliance maker might have different first principles than a physicist.

第一性原理并非一份永远成立的真理清单;我们对第一性原理的理解会随着认知的加深而改变。它们是我们赖以构建一切的基础,因此在每种情况下都会有所不同——但我们了解得越多,就越能提出质疑。例如,如果我们考虑如何提高冰箱的能源效率,热力学定律可以作为第一性原理。然而,理论化学家或物理学家可能想要探索熵,从而进一步将热力学第二定律分解为基本原理以及基于这些原理所做的假设。第一性原理是我们在任何特定情况下都必须遵循的界限,因此,就热力学而言,家电制造商的第一性原理可能与物理学家有所不同。

Techniques for Establishing First Principles

建立第一性原理的技术

If we never learn to take something apart, test our assumptions about it, and reconstruct it, we end up bound by what other people tell us is possible. We end up trapped in the way things have always been done. When the environment changes, we just continue as if things were the same, making costly mistakes along the way.

如果我们从未学会拆解事物、检验我们对它的假设并重新构建它,最终就会被他人告诉我们的“可能”所束缚。我们会困于墨守成规的思维模式中。当环境发生变化时,我们却依然故我,仿佛一切都未曾改变,从而犯下代价高昂的错误。

Some of us are naturally skeptical of what we’re told: Maybe it doesn’t match up to our experiences. Maybe it’s something that used to be true but isn’t true anymore. Or maybe we just think differently about something. When it comes down to it, everything that is not a law of nature is just a shared belief. Money is a shared belief. So is a border. So is Bitcoin. So is love. The list goes on.

我们有些人天生就对听到的东西持怀疑态度:也许它与我们的经验不符;也许它曾经是正确的,但现在不再正确;又或许我们只是对某些事情有不同的看法。归根结底,所有非自然规律的事物都只是一种共同的信念。金钱是一种共同的信念,边界也是如此,比特币也是如此,爱情也是如此。这样的例子不胜枚举。

There are two techniques we can use to change the level where we are looking at a situation, identify the first principles, and cut through the dogma and shared belief: Socratic questioning and the Five Whys.

我们可以使用两种技巧来改变我们看待事物的层面,找出基本原则,并打破教条和共同信念:苏格拉底式提问和五问法。

Socratic questioning: Socratic questioning can be used to establish first principles through stringent analysis. This is a disciplined questioning process used to establish truths, reveal underlying assumptions, and separate knowledge from ignorance. The key distinction between Socratic questioning and ordinary discussion is that the former seeks to draw out first principles in a systematic manner. Socratic questioning generally follows this process:

苏格拉底式提问:苏格拉底式提问可以通过严谨的分析来确立基本原理。这是一种有条理的提问过程,用于确立真理、揭示潜在假设,并将知识与无知区分开来。苏格拉底式提问与普通讨论的关键区别在于,前者旨在系统地引出基本原理。苏格拉底式提问通常遵循以下步骤:

  1. Clarifying your thinking and explaining the origins of your ideas. (Why do I think this? What exactly do I think?)

    理清你的思路,并解释你的想法来源。(我为什么这么想?我的想法究竟是什么?)

  2. Challenging assumptions. (How do I know this is true? What if I thought the opposite?)

    挑战既有假设。(我怎么知道这是真的?如果我的想法正好相反呢?)

  3. Looking for evidence. (How can I back this up? What are my sources?)

    我正在寻找证据。(我如何才能证实这一点?我的信息来源是什么?)

  4. Considering alternative perspectives. (What might others think? How do I know I am correct?)

    考虑其他观点。(其他人会怎么想?我怎么知道自己是对的?)

  5. Examining consequences and implications. (What if I am wrong? What are the consequences if I am?)

    审视后果和影响。(如果我错了怎么办?如果我错了,会有什么后果?)

  6. Questioning the original questions. (Why did I think that? Was I correct? What conclusions can I draw from the reasoning process?)

    对最初的问题提出质疑。(我为什么会这么想?我的想法正确吗?我能从推理过程中得出什么结论?)

Socratic questioning stops you from relying on your gut and limits strong emotional responses. This process helps you build something that lasts.

苏格拉底式提问能让你摆脱直觉的束缚,并限制强烈的情绪反应。这个过程有助于你建立持久的联系。

The Five Whys: The Five Whys is a method rooted in the behavior of children. Children instinctively think in first principles; just like us, they want to understand what’s happening in the world. To do so, they intuitively break through the fog with a game some parents have come to dread but that is exceptionally useful for identifying first principles: repeatedly asking “why.”

五问法:五问法是一种源于儿童行为的方法。孩子们本能地运用第一性原理思考;就像我们一样,他们渴望理解世界正在发生的事情。为了做到这一点,他们会本能地通过一种游戏来拨开迷雾——有些父母对此感到畏惧,但这种游戏对于识别第一性原理却异常有效:反复追问“为什么”。

The goal of the Five Whys is to traverse different levels until we land on a “what” or “how.” It is not about introspection, such as asking, “Why do I feel like this?” Rather, it is about systematically delving further into a statement or concept so that you can separate reliable knowledge from assumption. If your “whys” result in a statement of falsifiable fact, you have hit a first principle. If they end up with a “because I said so” or “it just is ,” you know you have landed on an assumption that may be based on popular opinion, cultural myth, or dogma. These are not first principles.

“五问法”的目标是逐层深入探究,最终找到“是什么”或“如何”。它并非内省,例如问“我为什么会有这种感觉?”,而是系统地深入挖掘某个陈述或概念,从而区分可靠的知识和假设。如果你的“为什么”最终指向一个可证伪的事实陈述,那么你就触及了第一原则。如果最终的答案是“因为我这么说”或“就是这样”,那么你就知道你陷入了一个假设,而这个假设可能基于流行观点、文化迷思或教条。这些都不是第一原则。

There is no doubt that both of these methods slow us down in the short term. They seem to get in the way of what we want to accomplish. We must pause, think, and research. And after we employ them a couple of times, we realize that often, after one or two questions, we are lost. We actually don’t know how to answer most of the questions. But when we are confronted with our own ignorance, we can’t just give up or resort to self-defense. If we do, we will never identify the first principles we have to work with and will instead make mistakes that will slow us down in the long term.

毫无疑问,这两种方法短期内都会拖慢我们的进度。它们似乎阻碍了我们达成目标。我们必须停下来思考、研究。然而,当我们尝试几次之后,就会发现,往往在提出一两个问题之后,我们就迷失了方向。事实上,我们根本不知道如何回答大多数问题。但是,当我们面对自身的无知时,我们不能就此放弃或采取自我保护的策略。如果我们这样做,就永远无法找到我们必须遵循的基本原则,反而会犯下长期阻碍我们前进的错误。

Science is much more than a body of knowledge. It is a way of thinking.

—Carl Sagan [3]

科学远不止是一套知识体系,它更是一种思维方式。——卡尔·萨根[3]

Using First Principles Thinking to Blow Past Inaccurate Assumptions

运用第一性原理思维摒弃不准确的假设

The discovery that a bacterium, not stress, causes the majority of stomach ulcers is a great example of what can be accomplished when we push past assumptions to get at first principles. For centuries following the discovery of bacteria, scientists thought that bacteria could not grow in the stomach, on account of its acidity. If you had surveyed doctors and medical research scientists in the 1960s or ’70s, they likely would have postulated this as a first principle. When a patient came in complaining of stomach pain, no one ever looked for a bacterial cause.

发现大多数胃溃疡是由细菌而非压力引起的,这是一个很好的例子,说明当我们突破固有观念,探寻基本原理时,能够取得怎样的成就。在细菌被发现后的几个世纪里,科学家们一直认为,由于胃部的酸性环境,细菌无法在胃中生长。如果你在20世纪60年代或70年代调查医生和医学研究人员,他们很可能会把这当作一条基本原理。当病人前来就诊,抱怨胃痛时,从来没有人会去探究细菌感染的可能性。

It turned out, however, that a sterile stomach was not a first principle—it was an assumption. As Kevin Ashton writes in his book on creativity, discovery, and invention, “the dogma of the sterile stomach said that bacteria could not live in the gut.” [4] Because this dogma was taken as truth, for a long time, no one ever looked for evidence that it could be false.

然而,事实证明,胃部无菌并非基本原理,而是一种假设。正如凯文·阿什顿在其关于创造力、发现和发明的著作中所写,“胃部无菌的教条认为细菌无法在肠道中生存。”[4] 由于这一教条长期以来被视为真理,因此没有人去寻找它可能是错误的证据。

That changed for good with the discovery of Helicobacter pylori bacterium and its role in stomach ulcers. When pathologist Robin Warren saw bacteria in samples from patients’ stomachs, he realized that stomachs were not, in fact, sterile. He started collaborating with Barry Marshall, a gastroenterologist, and together they found bacteria in loads of stomachs. If the sterile stomach wasn’t a first principle, then, when it came to stomachs, what was?

幽门螺杆菌的发现及其在胃溃疡中的作用彻底改变了这一切。病理学家罗宾·沃伦在患者胃部样本中发现细菌后,意识到胃并非无菌。他开始与胃肠病学家巴里·马歇尔合作,两人共同在大量胃部样本中发现了细菌。如果无菌胃并非基本原理,那么,对于胃而言,什么才是呢?

Marshall, in an interview with Discover , recounts that Warren gave him a list of twenty patients identified as possibly having cancer—but when Warren looked, he had found, instead, the same bacteria in all of them. He said, “Why don’t you look at their case records and see if they’ve got anything wrong with them?” Since they now knew stomachs weren’t sterile, they could question all the associated dogma about stomach disease and use some Socratic-type questioning to identify the first principles at play. They spent years challenging their related assumptions, clarifying their thinking, and looking for evidence. [5]

马歇尔在接受《发现》杂志采访时回忆说,沃伦给了他一份名单,上面列着20名疑似癌症患者——但沃伦检查后发现,他们体内都存在同一种细菌。他说:“你为什么不看看他们的病历,看看他们是不是有什么其他问题呢?”既然他们现在知道胃并非无菌,他们就可以质疑所有关于胃病的教条,并运用苏格拉底式的提问方法来探寻其中的基本原理。他们花了数年时间挑战相关的假设,澄清思路,并寻找证据。[5]

Their story ultimately had a happy ending: in 2005, Marshall and Warren were awarded the Nobel Prize, and now stomach ulcers are regularly treated effectively with antibiotics, improving and saving the lives of millions of people. But many practitioners and scientists rejected their findings for decades. The dogma of the sterile stomach was so entrenched as a first principle that it was hard for many to admit that it rested on some incorrect assumptions that ultimately ended with the explanation, “because that’s just the way it is.” Even though, as Ashton notes, “ H. pylori has now been found in medical literature dating back to 1875,” [6] it was Warren and Marshall who were able to show that “because I said so” wasn’t enough to count the sterile stomach as a first principle.

他们的故事最终迎来了圆满的结局:2005年,马歇尔和沃伦荣获诺贝尔奖,如今,胃溃疡已能通过抗生素得到有效治疗,改善并挽救了数百万人的生命。然而,几十年来,许多医生和科学家都拒绝接受他们的发现。无菌胃的教条根深蒂固,被视为第一原则,以至于许多人难以承认它建立在一些错误的假设之上,而这些假设最终只能用“因为事实就是如此”来解释。尽管正如阿什顿所指出的,“幽门螺杆菌的发现已追溯至1875年的医学文献”[6],但正是沃伦和马歇尔证明,“因为我这么说”并不足以将无菌胃视为第一原则。

Incremental Innovation and Paradigm Shifts

渐进式创新与范式转变

Understanding how and why something works is a key step to improving it. First principles thinking helps us avoid the problem of relying on someone else’s tactics without understanding the rationale behind them.

理解事物运作的原理是改进它的关键步骤。运用第一性原理思考可以帮助我们避免盲目照搬他人的策略,而不理解其背后的逻辑。

Temple Grandin is famous for a couple of reasons. First, she is autistic, and was one of the first people to publicly disclose this fact and give insight into the inner workings of one type of autistic mind. Second, she is a scientist who has developed many techniques to improve the welfare of livestock in the agricultural industry.

坦普尔·格兰丁之所以出名,有两个原因。首先,她是一位自闭症患者,也是最早公开披露这一事实并深入剖析自闭症患者心理运作机制的人之一。其次,她是一位科学家,开发了许多改善农业领域牲畜福利的技术。

One of the approaches Grandin pioneered was the curved cattle chute. Before her experiments, cattle were herded through a straight chute. Curved chutes, Grandin found, “are more efficient for handling cattle because they take advantage of the natural behavior of cattle. Cattle move through curved races more easily because they have a natural tendency to go back to where they came from.” [7] Of course, science doesn’t stop with one innovation, and animal scientists continue to study the best way to treat livestock animals.

格兰丁开创的方法之一是使用弯曲的牛栏。在她的实验之前,人们都是用直线型的牛栏来驱赶牛群。格兰丁发现,弯曲的牛栏“更有效地管理牛群,因为它利用了牛的自然习性。牛更容易通过弯曲的通道,因为它们天生就有返回原路的倾向。”[7] 当然,科学的进步不会止步于一项创新,动物科学家们仍在不断研究如何更好地对待牲畜。

Stockmanship Journal presented research that questioned the efficiency of Grandin’s curved chute. It demonstrated that sometimes, the much simpler straight chute would achieve the same effect in terms of cattle movement. The journal then sought out Grandin’s response, which is invaluable for teaching us the necessity of first principles thinking.

《畜牧学杂志》发表了一项研究,质疑格兰丁设计的弧形牛栏的效率。研究表明,有时,更简单的直形牛栏也能达到同样的牛群移动效果。该杂志随后联系了格兰丁,请他对此作出回应,而格兰丁的回应对于我们理解运用第一性原理思考的重要性具有不可估量的价值。

Grandin explained that curved chutes are not a first principle. She designed them as a tactic to address the first principle of animal handling that she identified in her research—essentially, that reducing stress to the animals is the single most important aspect of handling them and affects everything from their conception rates to their weight to their immune systems. When designing a livestock environment, she noted, a straight chute could work if it is part of a system that reduces stress to the animals. If you know the principles, you can change the tactics. [8]

格兰丁解释说,弯曲的通道并非首要原则。她设计弯曲通道是为了解决她在研究中发现的动物管理首要原则——即减少动物应激是动物管理中最重要的方面,它会影响动物的方方面面,从受孕率到体重再到免疫系统。她指出,在设计畜牧环境时,如果直通道是减少动物应激系统的一部分,那么它也可以发挥作用。如果你了解了这些原则,你就可以改变策略。[8]

Sometimes, we don’t want to fine-tune what is already there—we are skeptical, or curious, and are not interested in accepting what already exists as our starting point. When we start with the idea that the way things are might not be the way they have to be, we put ourselves in the right frame of mind to identify first principles. The real power of first principles thinking is moving away from random change and into choices that have a real possibility of success.

有时,我们并不想对现状进行微调——我们心存怀疑或好奇,不愿接受既有的事物作为出发点。当我们抱着“现状未必是它应有的样子”的想法出发时,我们就找到了识别基本原理的正确方法。基本原理思维的真正力量在于,它能帮助我们摆脱随机变化,做出真正有可能成功的选择。

As to methods, there may be a million and then some, but principles are few. The man who grasps principles can successfully select his own methods. The man who tries methods, ignoring principles, is sure to have trouble.

—Harrington Emerson [9]

方法或许数不胜数,但原则却寥寥无几。掌握原则的人能够成功地选择适合自己的方法。而忽略原则、盲目追求方法的人,注定会遇到麻烦。——哈灵顿·爱默生[9]

Conclusion

结论

First principles thinking is the art of breaking down complex problems into their most fundamental truths. It’s a way of thinking that goes beyond the surface and allows us to see things from a new perspective.

第一性原理思维是将复杂问题分解为最基本真理的艺术。它是一种超越表面现象的思维方式,使我们能够从全新的视角看待事物。

Thinking in terms of first principles allows us to identify the root causes and strip away the layers of complexity and focus on the most effective solutions. Reasoning from first principles allows us to step outside the way things have always been done and instead see what is possible.

从第一性原理出发思考,可以帮助我们找到问题的根本原因,剥离复杂的表象,从而专注于最有效的解决方案。从第一性原理出发进行推理,可以让我们跳出固有思维模式,探索各种可能性。

First principles thinking is not easy. It requires a willingness to challenge the status quo. This is why it’s often the domain of rebels and disrupters who believe there must be a better way. It’s the thinking of those who are willing to start from scratch and build from the ground up.

第一性原理思考并非易事。它需要挑战现状的意愿。正因如此,它往往是那些坚信一定有更好方法的叛逆者和颠覆者的专属领域。它是那些愿意从零开始、白手起家的人的思维方式。

In a world focused on incremental improvement, first principles thinking offers a competitive advantage because almost no one does it.

在一个注重渐进式改进的世界里,从第一性原理出发的思考方式能够提供竞争优势,因为几乎没有人这样做。

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Thought Experiment

思想实验

Imagine the possibilities.

想象一下各种可能性。

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Creativity is intelligence having fun.

—Anonymous [1]

创造力是智慧的乐趣。——佚名[1]
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Thought experiments can be defined as “devices of the imagination used to investigate the nature of things.” [2] Many disciplines, such as philosophy and physics, make use of thought experiments to examine what can be known. In doing so, they open new avenues for inquiry and exploration.

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思想实验可以定义为“运用想象力来探究事物本质的工具”。[2] 许多学科,例如哲学和物理学,都运用思想实验来检验我们能够了解什么。这样做,它们开辟了新的探究和探索途径。

Thought experiments are powerful because they help us learn from our mistakes and avoid future ones. They let us evaluate the potential consequences of our actions, take on the impossible, and reexamine history to make better decisions. They can help us figure out both what we really want and the best way to get there.

思想实验之所以强大,是因为它们能帮助我们从错误中吸取教训,避免重蹈覆辙。它们让我们评估自身行为的潜在后果,挑战看似不可能的任务,并重新审视历史以做出更明智的决策。它们还能帮助我们弄清楚自己真正想要的是什么,以及实现目标的最佳途径。

The Ovarian Lottery

卵巢彩票

We can use thought experiments to reveal blind spots.

我们可以利用思想实验来发现盲点。

Warren Buffett, one of the most famous investors in the history of the world, often uses thought experiments to educate. In pointing out the role of luck, he says, Imagine that it is twenty-four hours before you are going to be born, and a genie comes to you . [3]

沃伦·巴菲特是世界历史上最著名的投资者之一,他经常使用思想实验来进行教育。在指出运气的作用时,他说:“想象一下,在你出生前24小时,一个精灵来到你身边。”[3]

To further paraphrase this thought experiment: “The genie says you can determine the rules of the society you are about to enter and you can design anything you want. You get to design the social rules, the economic rules, the governmental rules. And those rules are going to prevail for your lifetime and your children’s lifetime and your grandchildren’s lifetime.”

进一步解释这个思想实验:“精灵说你可以决定你即将进入的社会的规则,你可以设计任何你想要的东西。你可以设计社会规则、经济规则、政府规则。而且这些规则将在你的一生、你的子孙后代的一生中都有效。”

“But,” he adds, “there is a catch.”

“但是,”他补充道,“这里有个问题。”

“You don’t know whether you’re going to be born rich or poor, male or female, infirm or able-bodied, in the United States or Afghanistan. All you know is that you get to take one ball out of a barrel.”

“你不知道自己会出生在美国还是阿富汗,是富有还是贫穷,是男性还是女性,是体弱多病还是身强力壮。你唯一知道的是,你只能从桶里抽取一个球。”

He goes on to tell you that through dumb luck, he and his business partner were born in the United States and, as a result, had a staggering advantage. He won the ovarian lottery.

他接着告诉你,他和他的商业伙伴纯属运气好,出生在美国,因此拥有巨大的优势。他中了卵巢彩票。

While how hard you work might improve your relative success, the ovarian lottery determines much of your absolute success.

虽然你的努力程度可能会提高你的相对成功率,但卵巢的遗传决定了你最终的成功率。

Betting on Basketball

篮球博彩

Suppose I asked you to tell me who would win in a game of basketball: NBA champion LeBron James or filmmaker Woody Allen? How much would you bet that your answer was correct?

假设我问你,NBA总冠军勒布朗·詹姆斯和电影导演伍迪·艾伦,谁会在一场篮球比赛中获胜?你觉得你的答案会是什么样?

I think you’d get me an answer quickly, and I hope you’d bet all you had.

我相信你会很快给我答复,而且我希望你会全力以赴。

Next, suppose I asked you to tell me who’d win in a game of basketball: NBA champion LeBron James or NBA champion Kevin Durant? How much would you bet that your answer was correct?

接下来,假设我问你,NBA总冠军勒布朗·詹姆斯和NBA总冠军凯文·杜兰特,谁会在一场篮球比赛中获胜?你觉得你的答案会是什么样?

A little harder, isn’t it? Would you bet anywhere near all you had on being right?

是不是有点难?你会拿你全部的积蓄去赌自己猜对吗?

Let’s think this through. You attempted to answer both questions in the same way—you imagined the contests. Perhaps more importantly, you didn’t attempt to answer either of them by calling up Messrs. James, Allen, and Durant and inviting them over for an afternoon of basketball. You simply simulated the games in your mind.

让我们仔细想想。你试图用同样的方法回答这两个问题——你想象了比赛场景。更重要的是,你并没有打电话给詹姆斯、阿伦和杜兰特,邀请他们来家里打一下午篮球。你只是在脑海中模拟了比赛。

In the first case, your knowledge of James (young, tall, athletic, and skilled), Allen (old, small, frail, and funny), and the game of basketball gave you a clear mental image. The disparity between the players’ abilities makes the question (and the bet) a total no-brainer.

在第一种情况下,你对詹姆斯(年轻、高大、运动能力强、技术精湛)、阿伦(年老、矮小、体弱、幽默)以及篮球比赛的了解,让你在脑海中构建出一幅清晰的画面。两位球员能力的巨大差距,使得这个问题(以及赌注)毫无悬念。

In the second case, your knowledge of James and Durant may well be extensive, but that doesn’t make it an easy bet. They’re both professional basketball players who are quite similar in size and ability, and both of them are likely to go down as among the best ever to play the game. It’s doubtful that one is much better than the other in a one-on-one match. The only way to answer the question for sure would be to see them play. And even then, a one-off contest is not going to be definitive.

第二种情况,你或许对詹姆斯和杜兰特非常了解,但这并不意味着你就能轻易下结论。他们都是职业篮球运动员,身材和技术都非常接近,而且都极有可能成为篮球史上最伟大的球员之一。一对一单挑的话,他们俩的实力差距很难说有多大。想要确切地回答这个问题,唯一的办法就是亲眼观看他们的比赛。即便如此,一场单打比赛的结果也无法最终定论。

A better way to answer the “who would win” question is through a remarkable ability of the human brain—the ability to conduct a detailed thought experiment. Its chief value is that it lets us do things in our heads we cannot do in real life, and so explore situations from more angles than we can physically examine and test for.

要回答“谁会赢”这个问题,更好的方法是利用人脑一项非凡的能力——进行细致的思维实验。它的主要价值在于,它让我们能够在脑海中完成现实生活中无法完成的事情,从而从比我们实际检验和测试所能达到的更多角度来探索各种情况。

Thought experiments are more than daydreaming. To be useful, they require the same rigor as a traditional experiment. Much like the scientific method, a thought experiment generally has the following steps:

思想实验并非只是白日做梦。要想发挥作用,它们需要像传统实验一样严谨。与科学方法类似,思想实验通常包含以下步骤:

  1. Ask a question.

    提出问题。

  2. Conduct background research.

    进行背景调查。

  3. Construct a hypothesis.

    提出假设。

  4. Test with (thought) experiments.

    用(思想)实验进行检验。

  5. Analyze outcomes and draw conclusions.

    分析结果并得出结论。

  6. Compare to hypothesis and adjust accordingly (new question, etc.).

    与假设进行比较并进行相应调整(例如,提出新问题等)。

In the James/Allen experiment above, we started with a question: Who would win in a game of basketball? If you didn’t already know who those people were, finding out would have been a necessary piece of background research. Then you would come out with your hypothesis (James all the way!) and think it through.

在上面提到的詹姆斯/艾伦实验中,我们首先提出了一个问题:谁会在篮球比赛中获胜?如果你事先不知道他们是谁,那么事先了解这些信息是必不可少的背景调查。然后,你就可以提出你的假设(詹姆斯绝对会赢!),并仔细思考。

One of the real powers of the thought experiment is that there is no limit to the number of times you can change a variable to see if it influences the outcome. In order to place your bet, you would want to estimate: In how many possible basketball games does Woody Allen beat LeBron James? Out of a hundred thousand game scenarios, Allen probably wins only in the few where LeBron starts the game by breaking an ankle. Experimenting to discover the full spectrum of possible outcomes gives you a better appreciation for what you can influence and what you can reasonably expect to happen.

这个思想实验的真正威力之一在于,你可以无限次地改变变量,观察它是否会影响结果。为了下注,你需要估算:伍迪·艾伦在多少场可能的篮球比赛中能击败勒布朗·詹姆斯?在十万种比赛场景中,艾伦可能只有在少数几场勒布朗开场就扭伤脚踝的情况下才能获胜。通过实验来探索所有可能的结果,能让你更好地理解你能影响什么,以及你能合理预期什么。

Let’s now explore a few areas in which thought experiments are tremendously useful.

现在让我们来探讨一下思想实验非常有用的几个领域。

  1. Imagining physical impossibilities

    想象物理上的不可能

  2. Reimagining history

    重新构想历史

  3. Intuiting the nonintuitive

    直觉上的非直觉

Imagining physical impossibilities: Albert Einstein was a great user of the thought experiment because it is a way to logically carry out a test in one’s own head that would be very difficult or impossible to perform in real life. With this tool, we can solve problems with intuition and logic whose conditions cannot be demonstrated physically.

想象物理上的不可能:阿尔伯特·爱因斯坦非常擅长运用思想实验,因为它提供了一种在脑海中逻辑地进行实验的方法,而这些实验在现实生活中很难甚至不可能进行。借助这种工具,我们可以运用直觉和逻辑来解决那些无法通过物理手段证明的问题。

One of Einstein’s notable thought experiments involved an elevator. [4] Imagine you were in a closed elevator, feet glued to the floor. Absent any other information, would you be able to know whether the elevator was in outer space, with a string pulling the elevator upward at an accelerating rate, or sitting on Earth, being pulled down by gravity? By running the thought experiment, Einstein concluded that you would not.

爱因斯坦著名的思想实验之一与电梯有关。[4] 想象一下,你身处一个封闭的电梯里,双脚被固定在地板上。在没有任何其他信息的情况下,你能判断出电梯是在外太空,被一根绳子加速向上拉动,还是在地球上,被重力向下牵引吗?通过这个思想实验,爱因斯坦得出结论:你无法判断。

This led to the formulation of Einstein’s second major theory, the general theory of relativity—his universal theory of gravity. Einstein’s hypothesis was that the force you feel from acceleration and the force you feel from gravity don’t just feel the same—they are the same! Gravity, he decided, must work similarly to the accelerating elevator. We can’t build elevators in space, but we can still define some of the properties they would have if we could. This gives us enough information to test the hypothesis. Eventually, Einstein worked it all out—mathematically and in great detail—but he started with a simple thought experiment, impossible to actually perform.

这促成了爱因斯坦第二大理论——广义相对论(即他的万有引力理论)的形成。爱因斯坦的假设是,你感受到的加速度和引力不仅感觉相同,它们本质上就是相同的!他认为,引力的运作方式必然类似于加速的电梯。我们无法在太空中建造电梯,但我们仍然可以定义一些如果可以建造电梯会具备的属性。这为我们提供了足够的信息来检验这个假设。最终,爱因斯坦用数学方法详细地推导出了所有结论,但他最初只是做了一个简单的思想实验,一个实际上不可能实现的实验。

This type of thought experiment need not apply only to physics and is reflected in some of our common expressions. When we say, “if money were no object” or “if you had all the time in the world,” we are asking someone to conduct a thought experiment, because removing that variable (money or time) is physically impossible. In reality, money is always an object, and we never have all the time in the world. But the act of detailing the choices we would make in these alternate realities that have properties otherwise similar to our current one—doing the thought experiment—is what leads to insights regarding what we value in life and where to focus our energies.

这种类型的思想实验并非物理学独有,它也体现在我们一些常用的表达方式中。当我们说“如果金钱不是问题”或“如果你拥有无限的时间”时,我们实际上是在邀请别人进行思想实验,因为在物理上,移除金钱或时间这两个变量是不可能的。现实中,金钱始终是一个客观存在的因素,而我们也永远不可能拥有无限的时间。但是,正是通过设想在这些与我们当前世界其他方面相似的平行世界中,我们会做出哪些选择——也就是进行思想实验——才能让我们更深刻地理解我们生活中真正珍视的是什么,以及我们应该将精力集中在哪里。

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Reimagining history: A familiar use of the thought experiment is to reimagine history. This one we all perform, all the time. What if I hadn’t been stuck at the airport bar where I met my future business partner? Would World War I have started if Serbian nationalist Gavrilo Princip hadn’t shot the archduke of Austria in Sarajevo? If Cleopatra hadn’t found a way to meet Caesar, would she still have been able to take the throne of Egypt?

重构历史:思想实验的一个常见用途就是重构历史。我们每个人都在不断地进行这种实验。如果我当初没有被困在机场酒吧里,没有遇到我未来的商业伙伴,那会怎样?如果塞尔维亚民族主义者加夫里洛·普林西普没有在萨拉热窝枪杀奥地利大公,第一次世界大战还会爆发吗?如果克利奥帕特拉没有找到与凯撒会面的方法,她还能登上埃及王位吗?

These approaches are called the historical counterfactual and semifactual . If Y happened instead of X, what would the outcome have been? Would the outcome have been the same?

这些方法被称为历史反事实分析和半事实分析。如果Y代替X发生,结果会是什么?结果会和X一样吗?

As popular—and generally useful—as counter- and semifactuals are, they are also the areas of thought experiment with which we need to use the most caution. Why? Because history is what we call a chaotic system, wherein a small change in the beginning conditions can cause a very different outcome down the line. This is where the rigor of the scientific method is indispensable if we want to draw conclusions that are useful.

尽管反事实和半事实论证很受欢迎,也通常很有用,但它们也是我们需要格外谨慎对待的思维实验领域。为什么呢?因为历史是一个混沌系统,初始条件的微小变化就可能导致最终截然不同的结果。正因如此,如果我们想要得出有用的结论,严谨的科学方法就显得不可或缺。

To understand it, let’s think about another chaotic system we’re all familiar with: the weather. Why is it that we can predict the movement of the stars but we can’t predict the weather more than a few weeks out, and even then, not altogether reliably? The reason is because weather is highly chaotic. Any infinitesimally small error in our calculations today will change the result down the line, as rapid feedback loops occur throughout time. Since our measurement tools are not infinitely accurate, and never will be, we are stuck with the unpredictability of chaotic systems.

为了理解这一点,我们不妨想想另一个大家都很熟悉的混沌系统:天气。为什么我们能预测星辰的运行轨迹,却只能预测几周后的天气,而且即便如此,预测结果也并非完全可靠?原因在于天气具有高度混沌性。我们今天计算中哪怕是微小的误差,都会在未来影响最终结果,因为快速的反馈循环会随着时间的推移而发生。由于我们的测量工具并非无限精确,而且永远不可能做到,我们只能接受混沌系统不可预测性的现实。

Compared to human systems, one could say weather is pretty reliable stuff. As anyone who’s seen Back to the Future knows, a small change in the past could have a massive, unpredictable effect on the future. Thus, running historical counterfactuals is an easy way to accidentally mislead yourself. We simply don’t know what else would have occurred had Cleopatra not met Caesar, or had you not been stuck at that airport. The potential outcomes are too chaotic.

与人类系统相比,天气可以说是相当可靠的。看过《回到未来》的人都知道,过去的一个微小改变可能会对未来产生巨大且不可预测的影响。因此,进行历史反事实推演很容易让人误入歧途。我们根本无法得知,如果克利奥帕特拉没有遇见凯撒,或者如果你没有被困在机场,事情会如何发展。所有可能的结果都太过混乱。

But we can use thought experiments to explore unrealized outcomes—to rerun a process as many times as we like in order to see what else could have occurred and learn more about the limits we have to work with.

但是我们可以使用思想实验来探索未实现的结果——根据我们的意愿多次重新运行一个过程,以看看还可能发生什么,并更多地了解我们必须面对的限制。

The events that happened in history are but one realization of the historical process— one possible outcome among a large variety of possible outcomes. They’re like a deck of cards that has been dealt only one time. All the things that didn’t happen, but could have if some little thing went another way, are invisible to us—that is, until we use our brains to generate these theoretical worlds via thought experiments.

历史事件不过是历史进程的一种体现——众多可能结果中的一种。它们就像一副只发过一次的扑克牌。所有那些没有发生,但如果某个细微的因素发生改变就可能发生的事情,对我们来说都是不可见的——除非我们运用大脑,通过思想实验来构建这些理论世界。

If we can also factor in the approximate probability of these occurrences, relative to the scope of all possible ones, we can learn what the most likely outcomes are. Sometimes, it is easy to imagine ten different ways a situation could have played out differently, but more of a stretch to change the variables and still end up with the same thing.

如果我们还能将这些事件发生的概率(相对于所有可能事件的范围)考虑在内,就能了解最可能的结果是什么。有时,我们很容易想象出某种情况可能出现的十种不同发展方式,但要改变所有变量却仍然得到相同的结果,就比较困难了。

So, let’s try it. Start with a question: What if Gavrilo Princip hadn’t shot Archduke Franz Ferdinand? That single act has often been credited with launching World War I, so it is a question worth asking. If we conclude the assassination started a chain reaction of which war was the inevitable result, it would certainly tell us a lot about certain causal relationships in politics, diplomacy, and possibly human psychology.

那么,我们不妨试一试。首先提出一个问题:如果加夫里洛·普林西普没有刺杀弗朗茨·斐迪南大公会怎样?这一举动常被认为是第一次世界大战的导火索,因此这个问题值得探讨。如果我们得出结论,认为刺杀事件引发了一系列连锁反应,最终导致战争,那么这无疑将揭示政治、外交乃至人类心理中某些因果关系的诸多奥秘。

Then we need to do our background research. What do we need to know to be able to answer this question? So we look into it—treaties, conflicts, alliances, interests, personalities—enough to be able to formulate a hypothesis.

接下来我们需要进行背景调查。我们需要了解哪些信息才能回答这个问题?所以我们要深入研究——条约、冲突、联盟、利益、人物——以便能够提出假设。

An immediate response to the assassination came two days later, on June 30, 1914. Austria changed its policy toward Serbia. Shortly after that, Germany offered full military support to Austria, and less than two months later, all of Europe was at war. Thus, a next step in our thought experiment might be to refine the question. Perhaps we’d ask something like, how did Princip’s assassination of the archduke influence Austrian policy toward Serbia?

刺杀事件发生两天后,即1914年6月30日,奥地利立即做出了回应。奥地利改变了对塞尔维亚的政策。此后不久,德国向奥地利提供了全面的军事支持,不到两个月后,整个欧洲就陷入了战争。因此,我们思想实验的下一步或许是细化问题。例如,我们可以问:普林西普刺杀斐迪南大公对奥地利对塞尔维亚的政策产生了怎样的影响?

Our hypothesis could be one of the following:

我们的假设可能是以下几种之一:

  1. The assassination had no effect on policy.

    这次暗杀事件对政策没有产生任何影响。

  2. The assassination had partial effect on policy.

    这次暗杀事件对政策产生了一定的影响。

  3. The assassination had total effect on policy.

    这次暗杀事件对政策产生了全面影响。

To test any one of these, we run the experiment in our heads. We sit back and think about what the world looked like in Sarajevo on June 28, 1914: the archduke and his wife being chauffeured in their car, Gavrilo Princip cleaning his gun somewhere. Now we imagine Princip gets stomach cramps from some bad food the night before. The archduke’s car makes it to its destination while Princip is curled up in bed. The archduke gives a speech, emphasizing peace. One of Princip’s gang tries to assassinate the archduke but fails. How does Austria react? Is the outcome demonstrably different from what they actually did?

为了检验这些假设,我们可以在脑海中进行实验。我们设想一下1914年6月28日萨拉热窝的景象:大公和他的妻子乘坐专车,加夫里洛·普林西普在某个地方擦拭着他的枪。现在我们假设普林西普因为前一天晚上吃了不干净的东西而胃痉挛。大公的专车顺利抵达目的地,而普林西普则蜷缩在床上。大公发表了一篇强调和平的演讲。普林西普的手下试图刺杀大公,但失败了。奥地利会作何反应?最终的结果与他们实际采取的行动是否明显不同?

Princip wasn’t a lone wolf, and there was a lot of resentment in Serbia toward Austria. How could the situation be changed to lead to a different Austrian policy? Given the climate at the time, is our hypothetical situation realistic? Meaning, can you construct a historically accurate scenario in which no events come to pass that prompt Austria’s policy change? How many Serbians would have to get the stomach flu?

普林西普并非孤军奋战,塞尔维亚国内对奥地利积怨已久。究竟怎样的局势才能改变奥地利的政策?考虑到当时的社会氛围,我们假设的情景是否现实?也就是说,你能否构建一个符合历史的场景,其中没有任何事件发生促使奥地利改变政策?究竟需要多少塞尔维亚人患上肠胃炎?

One of the goals of a thought experiment like this is to understand the situation enough to identify the decisions and actions that had impact. This process doesn’t provide definitive answers, such as whether the assassination did, or did not, cause World War I. What you are trying to get to is a rough idea of how much it may have contributed to starting the war. The more scenarios you can imagine where war comes to pass without the assassination, the weaker the case for it being the critical cause. Thus, by exploring the realistic relationships between events, you can better understand the most likely effects of any one decision.

这类思想实验的目标之一是充分理解情境,从而识别出产生影响的决策和行动。这个过程并不能提供确凿的答案,例如刺杀事件是否引发了第一次世界大战。我们试图了解的是,刺杀事件在多大程度上促成了战争的爆发。你能想象的战争在没有刺杀事件的情况下发生的场景越多,刺杀事件作为战争关键原因的论据就越弱。因此,通过探索事件之间现实的关联,你可以更好地理解任何一项决策最可能产生的后果。

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Intuiting the nonintuitive: One of the uses of thought experiments is to improve our ability to intuit the nonintuitive. In other words, a thought experiment allows us to verify whether our natural intuition is correct by running experiments in our deliberate, conscious minds that make a point clear.

洞察非直觉:思想实验的用途之一是提高我们洞察非直觉的能力。换句话说,思想实验允许我们通过在有意识的思考中进行实验来验证我们与生俱来的直觉是否正确,从而使某个观点变得清晰明了。

An example of this is the famous “veil of ignorance” proposed by philosopher John Rawls in his influential book A Theory of Justice . To figure out the most fair and equitable way to structure society, he proposed that the designers of said society operate behind a veil of ignorance. This meant that they could not know who they would be in the society they were creating. If they designed the society without knowing their economic status, their ethnic background, their talents and interests, or even their gender, they would have to put in place a structure that was as fair as possible in order to guarantee the best possible outcome for themselves. [6]

例如,哲学家约翰·罗尔斯在其影响深远的著作《正义论》中提出的著名“无知之幕”理论就是一个例子。为了找到构建社会最公平公正的方式,他提出社会的设计者应该在“无知之幕”的掩护下进行设计。这意味着他们不能预知自己在所创建的社会中会是什么样子。如果他们在不了解自身经济状况、种族背景、才能和兴趣,甚至性别的情况下设计社会,那么他们就必须建立一个尽可能公平的社会结构,以确保自身获得最佳结果。[6]

Our initial intuition regarding what is fair in a society is likely to be challenged during the “veil of ignorance” thought experiment. When confronted with the question of how best to organize society, we have a general feeling that it should be “fair.” But what exactly does this mean? We can use this thought experiment to test the likely outcomes of different rules and structures to come up with an aggregate of what is most fair.

在“无知之幕”思想实验中,我们最初对社会公平的直觉很可能会受到挑战。当被问及如何更好地组织社会时,我们通常会觉得社会应该“公平”。但这究竟意味着什么?我们可以利用这个思想实验来检验不同规则和结构可能带来的结果,从而得出最公平的综合方案。

We need not be constructing the legislation of entire nations for this type of thinking to be useful. Think, for example, of a company’s human resources policies on hiring, office etiquette, or parental leave. What kind of policies would you design or support if you didn’t know what your role in the company was, or even anything about who you were?

我们无需制定整个国家的法律才能使这种思维方式发挥作用。例如,想想一家公司的人力资源政策,包括招聘、办公室礼仪或育儿假。如果你不知道自己在公司里的角色,甚至对自己是谁一无所知,你会设计或支持什么样的政策呢?

Conclusion

结论

Thought experiments are the sandbox of the mind, the place where we can play with ideas without constraints. They’re a way of exploring the implications of our theories, of testing the boundaries of our understanding. They offer a powerful tool for clarifying our thinking, revealing hidden assumptions, and showing us unintended consequences.

思维实验是思维的沙盒,我们可以在这里不受限制地玩转各种想法。它们是一种探索理论含义、检验理解边界的方法。它们为我们提供了一种强有力的工具,帮助我们理清思路、揭示隐藏的假设,并展现意想不到的后果。

The power of thought experiments lies in their ability to create a simplified model of reality where we can test our ideas. In the real world, there are always confounding factors, messy details that obscure the core principles at work. But in a thought experiment, we can strip away the noise and focus on the essence of the problem.

思想实验的力量在于它能够构建一个简化的现实模型,让我们得以检验自己的想法。现实世界中总是存在各种干扰因素和繁杂的细节,这些都会掩盖核心原理。但在思想实验中,我们可以剔除这些干扰,专注于问题的本质。

Thought experiments offer a reminder that some of the most profound insights and innovations start with a simple question: What if?

思想实验提醒我们,一些最深刻的见解和创新都始于一个简单的问题:如果……会怎样?

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Supporting Idea:
支持观点:
Necessity and Sufficiency
必要性和充分性

We often make the mistake of assuming that having some necessary conditions in place means that we have the sufficient conditions in place for our desired event or effect to occur. The gap between the two is the difference between becoming a published author and becoming J. K. Rowling. Certainly, you have to know how to write well to become either, but knowing how to write well isn’t sufficient to guarantee you’ll become a Rowling. This is somewhat obvious to most. What’s not obvious is that the gap between what is necessary to succeed and what is sufficient is often luck, chance, or some other factor beyond your direct control.

我们常常误以为,具备某些必要条件就意味着具备了促成我们想要的结果或效果的充分条件。这两者之间的差距,正是成为出版作家和成为J·K·罗琳之间的区别。当然,要想成为其中任何一种人,你都必须具备良好的写作能力,但仅仅具备良好的写作能力并不足以保证你成为罗琳。这一点对大多数人来说显而易见。然而,不为人知的是,成功所需的条件和充分条件之间的差距,往往取决于运气、机遇或其他一些你无法直接控制的因素。

Assume you wanted to make it into the Fortune 500. Capital is necessary but not sufficient. Hard work is necessary but not sufficient. Intelligence is necessary but not sufficient. Billionaire success takes all of those things and more, plus a lot of luck. That’s a big reason that there’s no recipe for achieving it.

假设你想跻身财富500强。资金是必要的,但并非充分条件。努力是必要的,但并非充分条件。智慧是必要的,但并非充分条件。成为亿万富翁需要所有这些因素,甚至更多,外加大量的运气。这正是为什么没有通往亿万富翁之路的秘诀。

Winning a military battle is a great example of necessity and sufficiency. It is necessary to prepare for the battle by evaluating the strength and tactics of your enemy, and by developing your own plan. You need to address logistics, such as supply chains, and have a comprehensive strategy that allows flexibility to respond to the unexpected. These things, however, are not enough to win the battle. Without them, you definitely won’t be successful, but on their own they are not sufficient to guarantee success.

赢得一场军事战役是必要性和充分性的绝佳例证。战前准备至关重要,这包括评估敌军的实力和战术,并制定己方计划。你需要关注后勤保障,例如供应链,并制定一套能够灵活应对突发情况的全面战略。然而,这些并不足以赢得战役。缺少任何一项,你都肯定无法取得胜利;但仅凭这些也无法保证最终的胜利。

This concept is easily demonstrated in sports as well. To be successful at a professional level in any sport depends on some necessary conditions: you must be physically capable of meeting the demands of that sport, and have the time and means to train. Meeting these conditions, however, is not sufficient to guarantee a successful outcome. Many hardworking, talented athletes are unable to break into the professional ranks.

这个概念在体育运动中也很容易得到体现。要想在任何一项运动中取得职业成功,都取决于一些必要条件:你必须具备满足该项运动要求的身体素质,并且有时间和资源进行训练。然而,满足这些条件并不足以确保成功。许多勤奋刻苦、天赋异禀的运动员最终都无法跻身职业行列。

In mathematics, they call these groupings sets . The set of conditions necessary to become successful is a part of the set that is sufficient to become successful. But the sufficient set itself is far larger than the necessary set. Without that distinction, it’s too easy for us to be misled by the wrong stories.

在数学中,这些分组被称为集合。成功所需的必要条件集合是成功充分条件集合的一部分。但充分条件集合本身远大于必要条件集合。如果没有这种区分,我们就很容易被错误的说法所误导。

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Second-Order Thinking

二阶思维

What happens next?

接下来会发生什么?

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Technology is fine, but the scientists and engineers only partially think through their problems. They solve certain aspects, but not the total, and as a consequence it is slapping us back in the face very hard.

—Barbara McClintock [1]

技术固然好,但科学家和工程师们对问题的思考却往往片面。他们解决了某些方面的问题,却没有解决全部问题,结果就是,技术反过来狠狠地打了我们一巴掌。——芭芭拉·麦克林托克[1]
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Almost everyone can anticipate the immediate results of their actions. However, few people think about what happens next.

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几乎每个人都能预见到自己行为的直接后果。然而,很少有人会思考接下来会发生什么。

First-order thinking is easy and common. Second-order thinking is harder and requires thinking further ahead and thinking holistically. It requires us to consider not only our actions and their immediate consequences, but the subsequent effects of those actions as well. Failing to consider the second- and third-order effects of our decisions can unleash disaster.

一级思维简单易行,也十分常见。二级思维则更为困难,它需要我们进行更长远、更全面的思考。这要求我们不仅要考虑自身行为及其直接后果,还要考虑这些行为的后续影响。如果我们忽视了决策的二级和三级影响,就可能酿成灾难。

First-order thinking is almost always about satisfying the immediate problem. Second-order thinking, on the other hand, avoids problems before they happen by asking, “And then what?”

一级思维几乎总是着眼于解决眼前的难题。而二级思维则通过追问“然后呢?”来避免问题发生。

Without second-order thinking, it can be hard to appreciate just how often what appears to solve the immediate problem takes you further away from your objective. First-order thinking tells you the chocolate bar tastes good and will satisfy your cravings. Second-order thinking tells you that when the sugar high wears off, you’ll crash.

缺乏二阶思维,就很难意识到,看似能解决眼前问题的做法,往往会让你离目标越来越远。一阶思维告诉你,巧克力味道好,能满足你的口腹之欲。二阶思维则告诉你,糖分带来的快感消退后,你会感到疲惫不堪。

It is often easier to find examples of when second-order thinking didn’t happen—when people did not consider the effects of the effects. When someone tried to do something good, or even just benign, and instead brought calamity, we can safely assume the negative outcomes weren’t factored into their original thinking. Very often, the second level of effect is not considered until it’s too late. This concept is often referred to as the “Law of Unintended Consequences” for this very reason.

我们往往更容易找到缺乏二阶思维的例子——也就是人们没有考虑到后果的后果。当有人试图做好事,哪怕只是无害的举动,却反而带来了灾难时,我们可以肯定地说,他们最初的思考并没有考虑到这些负面结果。很多时候,人们直到为时已晚才意识到第二层后果。正因如此,这一概念通常被称为“非预期后果定律”。

We see examples of this oversight throughout history. The British are a well-intentioned nation with an ample supply of smart politicians. However, during its colonial rule of India, the British government began to worry about the number of venomous cobras in Delhi. To reduce the population, they instituted a reward for every dead snake brought to officials. In response, Indian citizens dutifully began breeding the snakes to slaughter and bring to officials. The snake problem became worse than when the government first intervened, because the British officials didn’t think at the second level.

纵观历史,这种疏忽屡见不鲜。英国人是一个出发点良好的国家,也拥有众多精明的政治家。然而,在殖民统治印度期间,英国政府开始担忧德里毒蛇的数量。为了减少蛇的数量,他们设立了一项奖励计划,奖励每一条被送上门的死蛇。作为回应,印度民众开始尽职尽责地饲养蛇,然后宰杀并交给官员。结果,蛇患比政府最初介入时更加严重,因为英国官员缺乏长远的考量。

Second-order effects occur even with something as simple as adding traction on tires: it seems like such a great idea, because the more traction you have, the less likely you are to slide, the faster you can stop, and, thus, the safer you are. However, the second-order effects are that your engine must work harder to propel the car, you get worse gas mileage (releasing more detrimental carbon dioxide into the atmosphere), and you leave more rubber particles on the road.

即使是增加轮胎抓地力这样简单的措施也会产生次级效应:这看似是个好主意,因为抓地力越大,车辆就越不容易打滑,刹车也就越快,从而更加安全。然而,次级效应在于:发动机需要更费力地驱动车辆,油耗增加(向大气中排放更多有害的二氧化碳),并且路面上会留下更多橡胶颗粒。

This is why any comprehensive thought process considers the effects of the effects of a decision seriously. You’re going to have to deal with them anyway. The genie never goes back in the bottle; you can never delete consequences to arrive back at the original starting conditions.

这就是为什么任何全面的思考过程都会认真考虑决策的后果。无论如何,你都必须面对这些后果。覆水难收,你永远无法抹去后果,回到最初的起点。

Stupidity is the same as evil if you judge by the results.

—Margaret Atwood [2]

如果以结果来判断,愚蠢与邪恶并无二致。——玛格丽特·阿特伍德[2]

In an example of second-order-thinking deficiency, we have been feeding antibiotics to livestock for decades, to make the resulting meat safer and cheaper. Only in recent years have we begun to realize that in doing so, we have helped create bacteria that we cannot defend against.

这就是缺乏二阶思维的一个例子:几十年来,我们一直给牲畜喂抗生素,以使肉类更安全、更便宜。直到最近几年,我们才开始意识到,这样做反而助长了我们无法抵御的细菌的滋生。

In 1963, UC Santa Barbara ecologist Garrett Hardin proposed his First Law of Ecology: “You can never merely do one thing.” [3] We operate in a world of multiple, overlapping connections, like a web, with many significant, yet obscure and unpredictable, relationships. Hardin developed second-order thinking into a tool, showing that if you don’t consider “the effects of the effects,” you can’t really claim to be doing any thinking at all.

1963年,加州大学圣巴巴拉分校的生态学家加勒特·哈丁提出了他的第一生态学定律:“你永远不可能只做一件事。”[3] 我们生活在一个由多重、重叠的联系构成的世界中,如同一张网,其中包含许多重要却又隐晦、难以预测的关系。哈丁将二阶思维发展成一种工具,他指出,如果你不考虑“影响的影响”,你就根本不能说你在进行任何思考。

When it comes to the overuse of antibiotics in meat, the first-order consequence is that the animals gain more weight per pound of food consumed, and thus, there is profit for the farmer. Animals are sold by weight, so the less food you need to use to bulk them up, the more profit you make when you go to sell them. The second-order effects, however, include many serious, negative consequences. The bacteria that survive this continued antibiotic exposure are antibiotic resistant. That means that the agricultural industry, when using these antibiotics as bulking agents, is allowing massive numbers of drug-resistant bacteria to become part of our food chain.

就肉类生产中抗生素的过度使用而言,最直接的后果是动物每摄入一磅饲料就能增重更多,从而为养殖户带来利润。动物按重量出售,因此,饲料用量越少,出售时的利润就越高。然而,其次,抗生素的滥用会带来许多严重的负面影响。长期接触抗生素后存活下来的细菌会产生耐药性。这意味着,农业生产中,抗生素作为增重剂的使用,实际上是让大量耐药菌进入了我们的食物链。

High degrees of connection make second-order thinking all the more critical, because denser webs of relationships make it easier for actions to have far-reaching consequences. You may be focused in one direction, not recognizing that the consequences of your decisions are rippling out all around you. Things are not produced and consumed in a vacuum.

高度的关联性使得二阶思维变得尤为重要,因为关系网络越紧密,行动就越容易产生深远的影响。你可能专注于某个方向,却意识不到你的决定会像涟漪一样扩散到你周围的各个角落。事物并非孤立地生产和消费。

When we try to pick out anything by itself, we find it hitched to everything else in the Universe.

—John Muir [4]

当我们试图单独看待任何事物时,会发现它与宇宙中的一切事物都息息相关。——约翰·缪尔[4]

Second-order thinking is not a way to predict the future. You are only able to think of the likely consequences of your decisions’ consequences based on the information available to you. However, this is not an excuse to power ahead and wait for post facto scientific analysis.

二阶思维并非预测未来之道。你只能根据现有信息推测决策可能带来的后果。然而,这并非鲁莽行事、坐等事后科学分析的借口。

Could the consequences of putting antibiotics in livestock feed have been anticipated? Likely, yes, by anyone with even a limited understanding of biology. We know that organisms evolve. They adapt based on environmental pressures, and those with shorter life cycles, like bacteria, can do it quite quickly, because they have more opportunities to do so. Antibiotics, by definition, kill bacteria. Bacteria, just like all other living things, want to survive. The pressures put on them by continued exposure to antibiotics increase their pace of evolution. Over the course of many generations, eventually, mutations will occur that allow certain bacteria to resist the effects of the antibiotics. These are the bacteria that will then reproduce more rapidly, creating the situation we are now in.

在牲畜饲料中添加抗生素的后果是否可以预见?很可能可以,任何稍懂生物学的人都能预见到。我们知道生物体会进化。它们会根据环境压力进行适应,而生命周期较短的生物,例如细菌,由于有更多机会进化,因此进化速度更快。抗生素的定义就是杀死细菌。细菌和其他所有生物一样,都渴望生存。持续接触抗生素给它们带来的压力会加速它们的进化。经过许多代,最终会发生突变,使某些细菌能够抵抗抗生素的作用。这些细菌随后会更快地繁殖,从而造成我们今天面临的局面。

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Second-order thinking teaches us two important concepts that underline the utility of this model. If we’re interested in understanding how the world works, we must think about second- and subsequent-level effects. We must understand that just because there is no immediate and visible impact from our decisions doesn’t mean that we are not moving closer to or further from our objectives. How often is short-term gain worth protracted, long-term pain?

二阶思维教会我们两个重要的概念,这两个概念凸显了该模型的实用性。如果我们想要了解世界的运行方式,就必须思考二阶及后续的影响。我们必须明白,仅仅因为我们的决策没有立即产生可见的影响,并不意味着我们没有朝着目标前进或后退。短期收益究竟有多少值得我们付出长期痛苦的代价?

Let’s look at two areas where second-order thinking can be used to great benefit:

让我们来看两个可以充分发挥二阶思维优势的领域:

  1. Prioritizing long-term interests over immediate gains

    优先考虑长远利益而非短期收益

  2. Constructing effective arguments

    构建有效论证

Prioritizing Long-Term Interests

优先考虑长期利益

Thinking long-term eliminates a lot of poor behavior. Most people prefer to give in to instant gratification. If we want to avoid problems, however, we need to see past the immediate moment and into the future. If we forgo the immediate pleasure of candy, we improve our long-term health. The first-order effect of candy is the amazing feeling triggered by an influx of pure sugar in our system. But what are the second-order effects of regular candy consumption? Is that what I want my body or life to look like in ten years? Second-order thinking involves asking ourselves if what we are doing now is moving us closer to or further away from our objectives.

长远思考可以避免很多不良行为。大多数人更倾向于追求即时满足。然而,如果我们想要避免问题,就需要超越眼前的利益,着眼于未来。如果我们放弃吃糖带来的即时快感,就能改善长期的健康。吃糖的第一层效应是体内大量纯糖带来的愉悦感。但是,经常吃糖的第二层效应是什么呢?十年后,我希望自己的身体或生活是这样的吗?第二层思考意味着要扪心自问:我们现在的所作所为,究竟是在让我们更接近目标,还是在让我们离目标更远?

The most dangerous form of short-term thinking is one that doesn’t understand that just because results are not visible doesn’t mean they are not accumulating. Thinking long-term helps us see how the accumulation of tiny gains or losses moves us toward or away from our intended future.

最危险的短视思维方式是,它不明白即使结果暂时不明显,也不代表它没有在积累。长远思考能帮助我们看到,微小的得失是如何一步步将我们推向或推离我们预期的未来。

Finding historical examples of second-order thinking can be tricky, because we don’t want to evaluate based solely on the outcome: “It all turned out well, so he must have thought through the consequences of his actions.” Even if you can glimpse the long-term gain from your short-term pain, there is no guarantee you’ll get there.

寻找二阶思维的历史例证可能很棘手,因为我们不想仅仅根据结果来评判:“事情最终都朝着好的方向发展了,所以他肯定考虑过自己行为的后果。” 即使你能从短期的痛苦中看到长期的收益,也不能保证你最终就能实现目标。

In 48 BC, Cleopatra of Egypt was in a terrible position. [6] Technically co-regent with her brother, in a family famous for murdering siblings, she was encamped in a swampy desert, ousted from the palace, with no solid plan for how to get back. She was queen, but she had made a series of unpopular decisions that left her with little political support and that gave her brother ample justification for trying to have her assassinated. What to do?

公元前48年,埃及艳后克利奥帕特拉处境艰难。[6] 名义上,她与哥哥共同执政,而她的家族素有弑兄之称。她被逐出宫廷,流亡在沼泽遍布的沙漠中,却没有任何切实可行的复辟计划。她虽是女王,但一系列不得人心的决定使她失去了政治支持,也给了她的哥哥充分的理由去刺杀她。她该怎么办?

At the same time, the great Roman general Caesar arrived in Egypt, chasing down his enemy Pompey and making sure the Egyptians knew who really was in charge on the Mediterranean. Egypt was an incredibly fertile, wealthy country, and as such was of great importance to the Romans. The way they inserted themselves in Egypt, however, made them extremely unpopular there.

与此同时,伟大的罗马将军凯撒抵达埃及,追击他的敌人庞培,并让埃及人明白谁才是地中海的真正统治者。埃及是一个极其富饶的国家,因此对罗马人至关重要。然而,罗马人强行介入埃及的方式却使他们在当地极不受欢迎。

To survive, Cleopatra had to make some tough decisions. Should she try to work things out with her brother? Should she try to marshal some support from another country? Or should she try to align herself with Caesar?

为了生存,克利奥帕特拉不得不做出一些艰难的决定。她应该尝试与她的兄弟和解吗?她应该尝试争取其他国家的支持吗?还是应该尝试与凯撒结盟?

In Cleopatra: A Life , Stacy Schiff explains that even in 48 BC, at the age of twenty-one, Cleopatra would have had a superb political education, based on both historical knowledge and firsthand exposure to the tumultuous events of life on the Mediterranean. She would have observed actions taken by her father, Auletes, as well as various family members, that resulted in exile, bribery, and murder from either a family member, the Romans, or the populace. She would have known that there were no easy answers. As Schiff explains, “What Auletes passed down to his daughter was a precarious balancing act. To please one constituency was to displease another. Failure to comply with Rome would lead to intervention. Failure to stand up to Rome would lead to riots.” [7]

在《克利奥帕特拉传》中,斯泰西·希夫解释说,即使在公元前48年,年仅21岁的克利奥帕特拉也已接受了卓越的政治教育,这既源于她丰富的历史知识,也源于她对地中海动荡局势的亲身经历。她目睹了父亲奥莱特斯以及其他家族成员的种种行为,这些行为最终导致了流放、贿赂,甚至被家族成员、罗马人或民众谋杀。她深知,世事无常。正如希夫所解释的:“奥莱特斯传授给女儿的是一种如履薄冰的平衡之道。取悦一方必然会得罪另一方。不服从罗马会导致罗马干预,而不反抗罗马则会导致暴乱。”[7]

In this situation, it was thus imperative that Cleopatra consider the second-order effects of her actions. Short-term gain might easily lead to execution (as indeed it already had for many of her relatives). If she wanted to be around for a while, she needed to balance her immediate goals of survival and possession of the throne with the future need for support to stay on it.

在这种情况下,克利奥帕特拉必须考虑其行为的深远影响。短期利益很容易导致她被处死(事实上,她的许多亲属已经因此丧命)。如果她想长久地活下去,就必须权衡眼前的生存和王位继承目标,以及未来维持王位所需的支持。

In 48 BC, Cleopatra chose to align herself with Caesar. The first-order effects of this decision, it seems likely she would have known: namely, that it would anger her brother, who would increase his plotting to have her killed, and that it would anger the Egyptian people, who didn’t want a Roman involved in their affairs. She probably anticipated that there would be short-term pain, and there was. Cleopatra effectively started a civil war, including a siege on the palace that left her and Caesar trapped there for months. In addition, she had to be constantly vigilant against the assassination schemes of her brother. So why did she do it?

公元前48年,克利奥帕特拉选择与凯撒结盟。她很可能预料到这一决定的直接后果:这会激怒她的哥哥,他会加紧策划刺杀她;也会激怒埃及人民,他们不愿让罗马人插手他们的事务。她或许预料到会有短暂的阵痛,而事实也的确如此。克利奥帕特拉实际上发动了一场内战,包括围攻皇宫,使她和凯撒被困数月之久。此外,她还必须时刻警惕哥哥的刺杀阴谋。那么,她为何要这样做呢?

We will never know for sure. We can only make an educated guess. But given that Cleopatra ruled Egypt quite successfully for many years after these events, her decision was probably based on seeing the effects of the effects: if she could somehow make it through the short-term pain, her leadership had a much greater chance of being successful with the support of Caesar and Rome than without it. As Schiff notes, “The Alexandrian War gave Cleopatra everything she wanted. It cost her little.” [8] In winning the civil war, Caesar got rid of all major opposition to Cleopatra and firmly aligned himself with her reign.

我们永远无法确切得知真相,只能做出合理的推测。但鉴于克利奥帕特拉在这些事件发生后成功统治埃及多年,她的决定很可能是基于对事件后果的考量:如果她能够渡过眼前的难关,那么在凯撒和罗马的支持下,她的统治成功的可能性将远大于没有支持的情况。正如希夫所指出的,“亚历山大战争给了克利奥帕特拉她想要的一切,而她几乎没付出什么代价。”[8] 凯撒赢得内战后,铲除了所有对克利奥帕特拉构成主要威胁的势力,并坚定地支持她的统治。

Being aware of second-order consequences and using them to guide your decision making may mean the short term is less spectacular, but the payoffs for the long term can be enormous. By delaying gratification now, you will save time in the future. You won’t have to clean up the mess you made on account of not thinking through the effects of indulging your short-term desires.

意识到次级后果并以此指导决策,或许意味着短期内收益不如预期,但长期回报却可能非常丰厚。延迟满足当下的欲望,将为你节省未来的时间。你无需为当初因未深思熟虑而放纵短期欲望所造成的后果而收拾残局。

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Constructing effective arguments: Second-order thinking can help you avert problems and anticipate challenges that you can then address in advance.

构建有效论证:二阶思维可以帮助你避免问题,预见挑战,从而提前应对。

For example, you construct arguments every day: convincing your boss to take a chance on a new product, convincing your spouse to try a new parenting technique. Life is filled with the need to be persuasive. Arguments are more effective when we demonstrate that we have considered the second-order effects of a decision and put effort into verifying that these are desirable as well.

例如,你每天都在构建论点:说服老板尝试新产品,说服配偶尝试新的育儿方法。生活中充满了说服的需要。当我们展现出已经考虑过决策的次要影响,并努力验证这些影响也是可取的时,论点会更加有效。

In late-eighteenth-century England, women had very few rights. Philosopher Mary Wollstonecraft was frustrated that this lack of rights limited a woman’s ability to be independent and make choices on how to live her life. Instead of arguing, however, for why women should have rights, she recognized that she had to demonstrate the value that these rights would confer. She explained the benefits to society that would be realized because of the granting of those rights. She argued for the education of women because it would, in turn, make them better wives and mothers, more able to both support themselves and raise smart, conscientious children.

在十八世纪末的英国,女性几乎没有任何权利。哲学家玛丽·沃斯通克拉夫特对此感到沮丧,因为这种权利的缺失限制了女性独立自主、选择生活方式的能力。然而,她并没有论证女性为何应该拥有权利,而是意识到自己必须展现这些权利所带来的价值。她阐述了赋予女性这些权利将给社会带来的益处。她主张女性接受教育,因为这反过来会使她们成为更好的妻子和母亲,更有能力养活自己,并培养聪明懂事的孩子。

Her thoughts, from her book A Vindication of the Rights of Woman , are a demonstration of second-order thinking:

她在《女权辩护》一书中提出的观点,体现了二阶思维:

Asserting the rights which women in common with men ought to contend for, I have not attempted to extenuate their faults; but to prove them to be the natural consequence of their education and station in society. If so, it is reasonable to suppose that they will change their character, and correct their vices and follies, when they are allowed to be free in a physical, moral, and civil sense. [10]

我主张女性与男性一样,理应享有争取自身权利的权利,但我并未试图为她们的过错开脱,而是要证明这些过错是她们所受教育和社会地位的自然结果。如果真是如此,那么我们有理由相信,当她们在身体、道德和公民意义上获得自由时,她们会改变自己的性格,改正自己的恶习和愚行。[10]

Empowering women was a first-order effect of recognizing that women should have rights. But by discussing the logical consequences this empowerment would have on society—the second-order effects—Wollstonecraft started a conversation that eventually resulted in what we now call feminism. Not only would women eventually get freedoms they deserved, they would become better women and better members of society.

赋予女性权力是认识到女性应该拥有权利的直接结果。但通过探讨这种赋权对社会产生的逻辑后果——即次要影响——伍尔斯通克拉夫特开启了一场对话,最终催生了我们今天所说的女权主义。女性不仅最终获得了她们应得的自由,而且成为了更优秀的女性,也成为了更优秀的社会成员。

A Word of Caution

一句忠告

Second-order thinking must be tempered in one important way: you can’t let it lead to the paralysis of the “slippery slope effect,” the idea that if we start with action A, everything after is a slippery slope down to hell, with an inevitable chain of consequences including B, C, D, E, and F.

二阶思维必须在一个重要方面加以约束:你不能让它导致“滑坡效应”的瘫痪,这种想法认为,如果我们从行动 A 开始,之后的一切都将滑向地狱,不可避免地会产生一系列后果,包括 B、C、D、E 和 F。

Garrett Hardin smartly addresses this danger in Filters Against Folly :

加勒特·哈丁在《过滤愚行》一书中巧妙地探讨了这种危险:

Those who take the wedge (Slippery Slope) argument with the utmost seriousness act as though they think human beings are completely devoid of practical judgment. Countless examples from everyday life show the pessimists are wrong…. If we took the wedge argument seriously, we would pass a law forbidding all vehicles to travel at any speed greater than zero. That would be an easy way out of the moral problem. But we pass no such law. [11]

那些对楔子论(滑坡谬误)极其认真的人,仿佛认为人类完全缺乏实际判断力。无数来自日常生活的例子表明,悲观主义者是错误的……如果我们认真对待楔子论,我们就会立法禁止所有车辆以任何大于零的速度行驶。这本应是解决道德问题的捷径。但我们并没有通过这样的法律。[11]

In practical life, everything has limits. Even if we consider secondary and subsequent effects, we can only go so far. During waves of prohibition fever in the United States and elsewhere, conservative abstainers have frequently made the case that taking even a first drink would be the first step toward a life of sin. They’re right: it’s true that drinking a beer might lead you to become an alcoholic. But not most of the time.

在现实生活中,凡事皆有限度。即便考虑到次要影响和后续后果,我们也只能做到一定程度。在美国和其他地区禁酒浪潮中,保守的禁酒主义者经常声称,哪怕只是喝第一杯酒,也是走向罪恶人生的第一步。他们的说法没错:喝啤酒的确有可能让你变成酒鬼。但这种情况并非总是如此。

Thus, we need to avoid the slippery slope and the analysis paralysis it can lead to. Second-order thinking needs to evaluate the most likely effects and their most likely consequences, checking our understanding of what the typical results of our actions will be. If we worried about all possible effects of the effects of our actions, we would likely never do anything, and we’d be wrong. How you balance the need for higher-order thinking with practical, limiting judgment must be taken on a case-by-case basis.

因此,我们需要避免陷入滑坡效应及其可能导致的分析瘫痪。二阶思维需要评估最可能的影响及其最可能的后果,检验我们对自身行为典型结果的理解。如果我们担忧自身行为所有可能的影响,我们可能什么都做不了,而且我们也会犯错。如何平衡高阶思维的需求与务实、有限的判断,必须根据具体情况而定。

Conclusion

结论

Second-order thinking is a method of thinking that goes beyond the surface level, beyond the knee-jerk reactions and short-term gains. It asks us to play the long game, to anticipate the ripple effects of our actions and to make choices that will benefit us not just today, but in the months and years to come.

二阶思维是一种超越表面层次、超越本能反应和短期利益的思维方式。它要求我们着眼长远,预见我们行为的连锁反应,并做出不仅对当下有益,而且对未来数月乃至数年都有益的选择。

Second-order thinking demands we ask: And then what?

二阶思维要求我们问:然后呢?

Think of a chess master contemplating her next move. She doesn’t just consider how the move will affect the next turn, but how it will shape the entire game. She’s thinking many steps ahead. She’s considering not just her own strategy, but her opponent’s likely response. This is second-order thinking in action.

想象一下一位国际象棋大师正在思考下一步棋。她不仅考虑这一步棋会如何影响下一回合,还会考虑它将如何塑造整个棋局。她考虑的是很多步之后的情况。她不仅考虑自己的策略,还考虑对手可能的反应。这就是二阶思维的体现。

In our daily lives, we’re often driven by first-order thinking. We make decisions based on what makes us happy now, what eases our current discomfort or satisfies our immediate desires.

在日常生活中,我们常常受第一层思维的驱动。我们根据当下能让我们快乐、缓解当前不适或满足眼前欲望的事情来做决定。

Second-order thinking asks us to consider the long-term implications of our choices, to make decisions based not just on what feels good now, but on what will lead to the best outcomes over time.

二阶思维要求我们考虑选择的长期影响,做出的决定不仅要基于当下感觉良好的事物,还要基于从长远来看能带来最佳结果的事物。

In the end, second-order thinking is about playing the long game. It’s about making choices not just for the next move, but for the entire journey.

归根结底,二阶思维是指着眼长远。它不仅关乎下一步的行动,更关乎整个过程的选择。

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Probabilistic Thinking

概率思维

What are the chances?

可能性有多大?

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The theory of probability is the only mathematical tool available to help map the unknown and the uncontrollable. It is fortunate that this tool, while tricky, is extraordinarily powerful and convenient.

—Benoit Mandelbrot [1]

概率论是唯一能够帮助我们理解未知和不可控因素的数学工具。幸运的是,尽管这个工具颇为复杂,但它却异常强大且方便。——贝努瓦·曼德尔布罗特[1]
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Probabilistic thinking is essentially trying to estimate, using some math and logic, the likelihood of any specific outcome occurring. It is one of the best tools we have to improve the accuracy of our decisions. In a world where each moment is determined by an infinitely complex set of factors, probabilistic thinking helps us deal with uncertainty. When we know these, our decisions can be more precise and effective.

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概率思维本质上是运用数学和逻辑来估算特定结果发生的可能性。它是我们提高决策准确性的最佳工具之一。在这个每个时刻都由无限复杂的因素决定的世界里,概率思维帮助我们应对不确定性。当我们掌握了这些因素,我们的决策就能更加精准有效。

Are You Going to Get Hit by Lightning or Not?

你到底会不会被闪电击中?

It’s worth asking why we need to think in probabilities at all. Things either are or are not, right? Either we will get hit by lightning today or we won’t . The problem is, we just don’t know until we live out the day—which doesn’t help us at all when we make our decisions in the morning about what to do. The future is far from predetermined, and we can better navigate it by understanding the likelihood of events that could impact us.

值得思考的是,我们为什么需要用概率来思考问题。事情要么发生,要么不发生,对吧?今天要么我们会被闪电击中,要么不会。问题在于,我们只有亲身经历才能知道结果——这在我们早上做决定时毫无帮助。未来远非预先注定,了解可能影响我们的事件发生的可能性,能让我们更好地应对未来。

Very few things are 100 percent certain. Nearly everything is a probability. Our lack of perfect information about the world gives rise to all of probability theory, and to its usefulness. We know now that the future is inherently unpredictable, because not all variables can be known, and even the smallest error in our data very quickly throws off our predictions. The best we can do is estimate the future by generating realistic, useful probabilities. So how do we do that?

极少有事情是百分之百确定的。几乎所有事情都存在概率。我们对世界的了解并不完美,这催生了概率论及其应用价值。我们现在知道,未来本质上是不可预测的,因为并非所有变量都能被掌握,而且即使数据中出现最小的误差也会迅速影响我们的预测。我们所能做的,就是通过生成切实可行的概率来估计未来。那么,我们该如何做到这一点呢?

Probability is everywhere, down to the very bones of the world. The probabilistic machinery in our minds—the cut-to-the-quick “heuristics” made so famous by the psychologists Daniel Kahneman and Amos Tversky—was evolved by the human species in a time before computers, factories, traffic, middle managers, and the stock market. It served us in a time when human life was about survival and still serves us well in that capacity.

概率无处不在,深入到世界的每一个角落。我们大脑中的概率机制——那些由心理学家丹尼尔·卡尼曼和阿莫斯·特沃斯基发扬光大的、直击要害的“启发式方法”——是人类在计算机、工厂、交通、中层管理人员和股票市场出现之前就已经进化形成的。在人类生活以生存为重的时代,它为我们提供了帮助,如今依然如此。

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But what about today—a time when, for most of us, survival is not so much the issue? Today, we want to thrive . We want to compete, and win. Mostly, we want to make good decisions in complex social systems that were not part of the world in which our brains evolved their (quite rational) heuristics.

但如今呢?对我们大多数人来说,生存不再是首要任务。如今,我们渴望蓬勃发展,渴望竞争,渴望胜利。最重要的是,我们渴望在复杂的社会系统中做出正确的决策,而这些系统并非我们大脑进化出(相当理性的)经验法则时所处的环境。

To achieve these aims, we need to consciously add in a layer of probability awareness to our thinking.

为了实现这些目标,我们需要有意识地在我们的思维中增加一层概率意识。

What is probability awareness, and how can you use it to your advantage? There are three important aspects of probability that we need to explain so you can integrate them into your thinking, to get you into the ballpark and improve your chances of catching the ball:

什么是概率意识?如何利用概率意识?我们需要解释概率的三个重要方面,以便您能将它们融入到您的思维中,从而帮助您大致了解概率,提高把握机会的几率:

  1. Bayesian thinking

    贝叶斯思维

  2. Fat-tailed curves

    肥尾曲线

  3. Asymmetries

    不对称性

Bayesian thinking: Thomas Bayes was an English minister in the first half of the eighteenth century, whose most famous work, “An Essay Toward Solving a Problem in the Doctrine of Chances,” was brought to the attention of the Royal Society by his friend Richard Price in 1763—two years after his death. The essay, the key to what we now know as Bayes’s Theorem, concerned how we should adjust probabilities when we encounter new data.

贝叶斯思想:托马斯·贝叶斯是十八世纪上半叶的一位英国牧师,他最著名的著作《论概率论中一个问题的解决》(An Essay Toward Solving a Problem in the Doctrine of Chances)于1763年由他的朋友理查德·普莱斯提交给皇家学会——此时距离他去世已两年。这篇论文是如今我们所知的贝叶斯定理的关键,它探讨了当我们遇到新数据时应该如何调整概率。

The core of Bayesian thinking (or Bayesian updating, as it can be called) is this: given that we have limited but useful information about the world, and are constantly encountering new information, we should consider what we already know—as much of it as possible—when we learn something new. Bayesian thinking allows us to use all relevant prior information in making decisions. Statisticians might call it a “base rate”—taking in outside information about past situations like the one you’re in.

贝叶斯思维(或者也可以称之为贝叶斯更新)的核心在于:鉴于我们对世界的认知信息有限但有用,并且不断接触到新的信息,我们在学习新知识时应该尽可能多地考虑已有的知识。贝叶斯思维使我们能够利用所有相关的先验信息来做决策。统计学家可能会称之为“基准率”——它包含了关于过去类似情况的外部信息。

Consider the headline “Violent Stabbings on the Rise.” Without Bayesian thinking, you might become genuinely afraid, because your chance of being a victim of assault or murder is higher than it was a few months ago. But a Bayesian approach will have you putting this information into the context of what you already know about violent crime: You know that violent crime has declined to its lowest rates in decades. Your city is safer now than it has been since this measurement was started. Let’s say your chance of being a victim of a stabbing last year was 1 in 10,000, or 0.01 percent. The article states, with accuracy, that violent crime has doubled. Your chance of being stabbed is now 2 in 10,000, or 0.02 percent. Is that worth being terribly worried about? The prior information here is key. When we factor it in, we realize that our safety has not really been compromised.

想想“暴力刺伤事件上升”这个标题。如果没有贝叶斯思维,你可能会真的感到害怕,因为你成为袭击或谋杀受害者的概率比几个月前更高了。但贝叶斯方法会让你把这个信息放在你已知的暴力犯罪背景下进行分析:你知道暴力犯罪率已经下降到几十年来的最低水平。你所在的城市现在比这项统计开始以来任何时候都更安全。假设你去年被刺伤的概率是万分之一,也就是0.01%。文章准确地指出,暴力犯罪率翻了一番。你现在被刺伤的概率是万分之二,也就是0.02%。这值得你过度担忧吗?关键在于先验信息。当我们把这些信息考虑进去时,我们会意识到我们的安全并没有真正受到威胁。

If we look at diabetes statistics in the United States, our application of prior knowledge would lead us to a different conclusion. Here, a Bayesian analysis indicates you should be concerned. In 1958, 0.93 percent of the population was diagnosed with diabetes. In 2015, it was 7.4 percent. When you look at the intervening years, the climb in diabetes diagnoses is steady, not a spike. So the prior relevant data, or “priors,” indicate a trend that is worrisome.

如果我们查看美国的糖尿病统计数据,运用先验知识会得出不同的结论。贝叶斯分析表明,我们应该对此感到担忧。1958年,0.93%的人口被诊断患有糖尿病。到了2015年,这一比例上升至7.4%。纵观这两年,糖尿病诊断率的增长是稳步上升的,而非突然激增。因此,相关的先验数据,或者说“先验概率”,表明了一种令人担忧的趋势。

It is important to remember that priors themselves represent probability estimates. For each bit of prior knowledge, you are not putting it in a binary structure, saying it is true or not. You’re assigning it a probability of being true. Therefore, you can’t let your priors get in the way of processing new knowledge. In Bayesian terms, this is called the “likelihood ratio” or the “Bayes factor.” Any new information you encounter that challenges a prior simply means that the probability of that prior being true may be reduced. Eventually, some priors are replaced completely. Bayesian thinking is an ongoing cycle of challenging and validating what you believe you know. When making uncertain decisions, it’s nearly always a mistake not to ask: What are the relevant priors? What might I already know that I can use to better understand the reality of the situation?

重要的是要记住,先验本身代表概率估计。对于每一条先验知识,你并非将其置于二元结构中,断言它是真还是假,而是赋予它一个为真的概率。因此,你不能让先验妨碍你处理新知识。在贝叶斯理论中,这被称为“似然比”或“贝叶斯因子”。任何挑战先验的新信息都意味着该先验为真的概率可能会降低。最终,一些先验会被完全取代。贝叶斯思维是一个不断挑战和验证你自认为已知信息的循环过程。在做出不确定的决策时,几乎总是应该问自己:相关的先验是什么?我可能已经知道哪些信息可以用来更好地理解实际情况?

Fat-tailed curves: Many of us are familiar with the bell curve, that nice, symmetrical wave that captures the relative frequency of so many things from heights to exam scores. The bell curve is great because it’s easy to understand and easy to use. Its technical name is “normal distribution.” If we know we are in a bell curve situation, we can quickly identify our parameters and plan for the most likely outcomes.

肥尾曲线:我们很多人都熟悉钟形曲线,这种漂亮的对称波形可以很好地描述从身高到考试成绩等诸多事物的相对频率。钟形曲线的优点在于它易于理解和使用。它的专业名称是“正态分布”。如果我们知道当前情况符合钟形曲线,就可以快速确定参数并针对最可能出现的结果制定计划。

Fat-tailed curves are different. Let’s take a look.

厚尾曲线有所不同。我们来看一下。

Always be extra mindful of the tails: They might mean everything.

务必格外注意牌的尾部:它们可能意味着一切。

At first glance, the two figures seem similar enough. Common outcomes cluster together, creating a wave. The difference is in the tails. In a bell curve, the extremes are predictable. There can only be so much deviation from the mean. In a fat-tailed curve, there is no real cap on extreme events.

乍看之下,这两个图形似乎非常相似。常见结果聚集在一起,形成波浪状。区别在于尾部。在正态分布曲线中,极端值是可以预测的,偏离均值的幅度是有限的。而在厚尾分布曲线中,极端事件的数量没有真正的上限。

The more extreme events that are possible, the longer the tails of the curve get. Any one extreme event is still unlikely, but the sheer number of options means that we can’t rely on the most common outcomes as representing the average. The more extreme events that are possible, the higher the probability that one of them will occur. Crazy things are going to happen, and we have no way of identifying when.

极端事件的可能性越多,曲线的尾部就越长。任何单一的极端事件发生的概率仍然很低,但选项之多意味着我们不能依赖最常见的结果来代表平均水平。极端事件的可能性越多,其中某个极端事件发生的概率就越高。疯狂的事情终将发生,而我们却无法预知它们何时会发生。

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Think of it this way: In a bell curve situation, such as displaying the distribution of heights or weights in a human population, there are outliers on the spectrum of possibility, but the outliers have a fairly well-defined scope. You’ll never meet a man who is ten times the size of an average man. But in a curve with fat tails, like wealth, the central tendency does not work the same way. You may regularly meet people who are ten, a hundred, or ten thousand times wealthier than the average person. That is a very different type of world.

不妨这样想:在正态分布曲线中,例如展示人群的身高或体重分布,虽然存在一些异常值,但这些异常值的范围相当明确。你永远不会遇到一个体型是普通人十倍的人。但在像财富分布这样具有肥尾的曲线中,中心趋势就并非如此运作。你可能会经常遇到比普通人富有十倍、一百倍甚至一万倍的人。那是一个截然不同的世界。

Let’s reapproach the example of the risk of violence we discussed in relation to Bayesian thinking. Suppose you heard that you had a greater risk of slipping on the stairs and cracking your head open than being killed by a terrorist. The statistics, the priors, seem to back it up: a thousand people slipped on the stairs and died last year in your country, and only five hundred died in terrorist attacks. Should you be more worried about stairs or terror events? Some people use examples like these to prove that terror risk is low—since the recent past shows very few deaths, why worry? [3] The problem is in the fat tails: The risk of terror violence is more like wealth, while stair-slipping deaths are more like height and weight. In the next ten years, how many events are possible? How fat is the tail?

让我们重新审视一下之前讨论过的暴力风险与贝叶斯思维之间的关系。假设你听说,你滑倒摔破头的风险比被恐怖分子杀害的风险更大。统计数据和先验概率似乎也支持这一说法:去年在你所在的国家,有1000人滑倒摔死,而恐怖袭击致死人数只有500人。那么,你更应该担心楼梯事故还是恐怖袭击呢?有些人用类似的例子来证明恐怖袭击的风险很低——既然最近的死亡人数很少,为什么还要担心呢?[3] 问题在于分布的“肥尾”:恐怖暴力事件的风险更像是财富,而滑倒摔死的风险更像是身高体重。未来十年,可能发生多少起此类事件?分布的“肥尾”有多长?

The important thing is not to sit down and imagine every possible scenario in the tail (which, by definition, is impossible) but to deal with fat-tailed domains in the correct way: by positioning ourselves to survive or even benefit from the wildly unpredictable future, by being the only ones thinking correctly and planning for a world we don’t fully understand.

重要的是不要坐下来想象尾部所有可能的情况(根据定义,这是不可能的),而是要以正确的方式处理肥尾领域:通过调整自身位置,以便在难以预测的未来中生存甚至受益,成为唯一正确思考并为我们尚未完全了解的世界做好规划的人。

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Asymmetries: Finally, you need to think about something we might call “metaprobability”—the probability that your probability estimates themselves are any good.

不对称性:最后,你需要考虑一些我们可以称之为“元概率”的东西——你的概率估计本身是否有效的概率。

This massively misunderstood concept has to do with asymmetries. If you look at nicely polished stock pitches made by professional investors, nearly every time an idea is presented, the investor looks their audience in the eye and states that they think they’re going to achieve a rate of return of 20 to 40 percent per annum, if not higher. Yet exceedingly few of them ever attain that mark. It’s not because they don’t pick any winners—it’s because they get so many so wrong. They are consistently overconfident in their probabilistic estimates. (For reference, the general stock market in the United States, over a long period, has returned no more than 7 percent to 8 percent per annum, before fees.)

这个被严重误解的概念与不对称性有关。如果你仔细观察专业投资者精心准备的股票推介,你会发现几乎每次提出投资想法时,他们都会直视听众的眼睛,声称自己预计能获得20%到40%的年回报率,甚至更高。然而,真正能达到这个目标的人却寥寥无几。这并非因为他们选错了股票——而是因为他们错得离谱。他们总是对自己的概率估计过于自信。(作为参考,长期以来,美国股市的整体年回报率(扣除费用前)从未超过7%到8%。)

Another common asymmetry is people’s ability to estimate the effect of traffic on travel time. How often do you leave “on time” and arrive 20 percent early? Almost never? How often do you leave “on time” and arrive 20 percent late? All the time? Exactly. Your estimation errors are asymmetric, skewing in a single direction. This is often the case with probabilistic decision making. [5]

另一个常见的不对称性是人们对交通状况对出行时间影响的估计能力。你准时出发却提前20%到达的频率有多高?几乎没有?你准时出发却迟到20%的频率有多高?总是如此?没错。你的估计误差是不对称的,偏向于单一方向。这种情况在概率决策中经常出现。[5]

Far more probability estimates are wrong on the “over-optimistic” side than the “under-optimistic” side. You’ll rarely read about an investor who aimed for 25 percent annual return rates and who subsequently earned 40 percent over a long period of time, whereas you can throw a dart at The Wall Street Journal and hit the names of lots of investors who aim for 25 percent per annum with each investment and end up closer to 10 percent.

过于乐观的概率估计远比过于保守的概率估计更容易出错。你很少会看到有投资者设定25%的年回报率目标,最终却在长期投资中获得了40%的回报;然而,你随便翻翻《华尔街日报》,就能找到很多投资者,他们每次投资都设定25%的年回报率目标,最终却只有10%左右。

The Spy World

间谍世界

Successful spies are very good at probabilistic thinking. High-stakes survival situations tend to make us evaluate our environment with as little bias as possible.

成功的间谍非常擅长概率思维。高风险的生存情境往往会促使我们尽可能客观地评估周围环境。

When Vera Atkins was second in command of the French unit of the Special Operations Executive (SOE), a British intelligence organization during World War II that reported directly to Winston Churchill, [6] she had to make hundreds of decisions by figuring out the probable accuracy of inherently unreliable information.

二战期间,英国情报机构特别行动执行处(SOE)直接向温斯顿·丘吉尔汇报工作,当时维拉·阿特金斯担任SOE法国分队的副指挥官[6],她必须通过计算本质上不可靠的信息的可能准确性来做出数百个决定。

Atkins was responsible for the recruitment of British agents and their deployment into occupied France. She had to decide who could do the job and where the best sources of intelligence were. These were literal life-and-death decisions, and all were based in probabilistic thinking.

阿特金斯负责招募英国特工并将他们部署到被占领的法国。她必须决定谁能胜任这项工作,以及哪里有最好的情报来源。这些都是关乎生死的重要决定,而且所有决定都基于概率思维。

First, how do you choose a spy? Not everyone can go undercover in high-stress situations and make the contacts necessary to gather intelligence. The result of failure in France during the war was not getting fired; it was death. What factors of personality and experience show that a person is right for that job? Even today, with advancements in psychology, interrogation, and polygraph tests, it’s still a judgment call.

首先,如何挑选间谍?并非人人都能在高压环境下执行卧底任务,并建立必要的人脉来收集情报。二战期间,在法国,间谍失败的后果不是被解雇,而是死亡。什么样的性格和经验因素表明一个人适合这份工作?即使在今天,心理学、审讯技巧和测谎技术都取得了长足进步,这仍然是一项需要主观判断的工作。

For Vera Atkins, in the 1940s, it was very much a process of assigning weight to the various factors and coming up with a probabilistic assessment of who had a decent chance of success. Who spoke French? Who had the necessary confidence? Who was too tied to family? Who had the problem-solving capabilities? From recruitment to deployment, her development of each spy was a series of continually updated educated estimates.

对维拉·阿特金斯而言,在20世纪40年代,招募间谍很大程度上是一个权衡各种因素并做出概率评估的过程,以此判断谁有较大的成功几率。谁会说法语?谁具备必要的自信?谁过于顾家?谁有解决问题的能力?从招募到部署,她对每位间谍的培养都是一系列不断更新的、基于经验的评估。

Getting an intelligence officer ready to go is only half the battle. Where do you send them? If your information was so great that you knew exactly where to go, you probably wouldn’t need an intelligence mission. Choosing a target is another exercise in probabilistic thinking. You need to evaluate the reliability of the information you have and the networks you have set up. Intelligence is not evidence. There is no chain of command or guarantee of authenticity.

让情报人员做好准备只是成功的一半。接下来该派他们去哪里?如果你掌握的情报如此可靠,能够精确地知道该去哪里,那你可能根本就不需要情报任务了。选择目标本身就是概率思维的又一体现。你需要评估你掌握的信息和已建立的网络的可靠性。情报并非证据。它没有指挥链,也无法保证其真实性。

The stuff coming out of German-occupied France was at the level of grainy photographs, handwritten notes that passed through many hands on the way back to headquarters, and unverifiable wireless messages sent quickly, sometimes sporadically, and with the operator under incredible stress. When deciding what to use, Atkins had to consider the relevance, quality, and timeliness of the information she had.

从德占法国传回的信息质量参差不齐,包括模糊不清的照片、经多人转手送回总部的手写笔记,以及无法核实的无线电报。这些无线电报发送迅速,有时甚至断断续续,而且操作员承受着巨大的压力。在决定使用哪些信息时,阿特金斯必须考虑信息的关联性、质量和时效性。

She also had to make decisions based not only on what had happened but on what possibly could. Trying to prepare for every eventuality would mean that spies would never leave home, but they had to somehow prepare for a good deal of the unexpected. After all, a spy’s job is often executed in highly volatile, dynamic environments. The women and men Atkins sent over to France worked in three primary occupations: organizers were responsible for recruiting locals, developing the network, and identifying sabotage targets; couriers moved information all around the country, connecting people and networks to coordinate activities; and wireless operators had to set up heavy communications equipment, disguise it, get information out of the country, and be ready to move at a moment’s notice. All these jobs were dangerous. The full scope of the threats was never completely identifiable. There were so many things that could go wrong, so many possibilities for discovery or betrayal, that it was impossible to plan for them all. The average life expectancy in France for one of Atkins’s wireless operators was six weeks.

她不仅要根据已经发生的事情做出决定,还要根据可能发生的事情做出决定。试图为每一种可能的情况都做好准备,意味着间谍永远无法离开家,但他们必须想办法应对许多意想不到的情况。毕竟,间谍的工作通常是在高度动荡、瞬息万变的环境中进行的。阿特金斯派往法国的男女主要从事三项工作:组织者负责招募当地人、发展网络和确定破坏目标;信使在全国各地传递信息,连接人员和网络以协调行动;无线电操作员则必须架设笨重的通信设备,对其进行伪装,将信息传递出境,并随时准备行动。所有这些工作都充满危险。威胁的全部范围永远无法完全确定。可能出错的事情太多,被发现或背叛的可能性也太多,因此不可能面面俱到地做好计划。阿特金斯派往法国的无线电操作员的平均寿命只有六周。

Finally, the numbers suggest an asymmetry in the estimation of the probability of success of each individual agent. Of the four hundred agents that Atkins sent over to France, a hundred were captured and killed. This is not meant to pass judgment on her skills or smarts. Probabilistic thinking can only get you in the ballpark. It doesn’t guarantee 100 percent success.

最后,这些数字表明,对每个特工成功概率的估计存在不对称性。阿特金斯派往法国的四百名特工中,有一百名被俘并被杀。这并非意在评判她的能力或智慧。概率思维只能提供大致的估计,并不能保证百分之百的成功。

There is no doubt that Atkins relied heavily on probabilistic thinking to guide her decisions in the challenging quest to disrupt German operations in France during World War II. It is hard to evaluate the success of an espionage career, because it is a job that comes with a lot of loss. Atkins was extremely successful in that her network conducted valuable sabotage to support the Allied cause during the war, but the loss of life this work entailed was significant.

毫无疑问,在二战期间破坏德军在法国的行动这一充满挑战的任务中,阿特金斯大量运用概率思维来指导她的决策。间谍生涯的成功难以评判,因为这项工作伴随着巨大的损失。阿特金斯的间谍网络在战争期间为盟军开展了卓有成效的破坏活动,这无疑是极其成功的,但这项工作也造成了惨重的生命损失。

Conclusion

结论

Probabilistic thinking is the art of navigating uncertainty. Successfully thinking in shades of probability means roughly identifying what matters, coming up with a sense of the odds, doing a check on our assumptions, and then deciding.

概率思维是应对不确定性的艺术。成功地运用概率思维意味着大致确定哪些因素重要,估算概率,检验我们的假设,然后做出决定。

The challenge of probabilistic thinking is that it requires constant updating. As new information emerges, the probabilities change. What seemed likely yesterday may seem unlikely today. This both explains why probabilistic thinkers are always revising their beliefs with new data and why it’s so uncomfortable for many people.

概率思维的挑战在于它需要不断更新。随着新信息的出现,概率也会随之改变。昨天看似很有可能的事情,今天可能就显得不太可能了。这既解释了为什么概率思维者总是需要根据新数据修正他们的信念,也解释了为什么这种思维方式会让很多人感到不适。

It’s much easier to believe something false is true than deal with the fact that it might not be true. Being a probabilistic thinker means being willing to say, “I don’t know for sure, but based on the evidence, I think there’s a 63 percent chance of X.”

相信错误的事情为真远比面对它可能并非事实要容易得多。概率思维意味着愿意说:“我不能确定,但根据现有证据,我认为X发生的概率为63%。”

The rewards of probabilistic thinking are immense. By embracing uncertainty, we can make better decisions, avoid the pitfalls of overconfidence, and navigate complex situations with greater skill and flexibility. We can be more open-minded, more receptive to new ideas, and more resilient in the face of change.

概率思维的益处是巨大的。通过拥抱不确定性,我们可以做出更明智的决策,避免过度自信的陷阱,并以更高的技巧和灵活性应对复杂局面。我们可以更加开放包容,更容易接受新思想,并在面对变化时更具韧性。

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Supporting Idea:
Causation vs. Correlation

支持观点:因果关系与相关性

Confusion between these two terms often leads to a lot of inaccurate assumptions about the way the world works. We notice two things happening at the same time (correlation) and mistakenly conclude that one causes the other (causation). We then often act upon that erroneous conclusion, making decisions that can have immense influence across our lives. The problem is, without a good understanding of what is meant by these terms, these decisions fail to capitalize on real dynamics in the world and instead are rendered successful only by luck.

混淆这两个术语常常导致我们对世界运行方式产生许多不准确的假设。我们注意到两件事同时发生(相关性),却错误地得出结论,认为其中一件事导致另一件事(因果关系)。然后,我们常常基于这种错误的结论采取行动,做出可能对我们的人生产生巨大影响的决定。问题在于,如果对这两个术语的含义缺乏透彻的理解,这些决定就无法利用世界的真实动态,而仅仅依靠运气才能成功。

No Correlation

无相关性

The correlation coefficient between two measures, which varies between −1 and 1, is a measure of the relative weight of the factors they share. For example, two phenomena with few shared factors, such as bottled-water consumption versus suicide rate, should have a correlation coefficient of close to 0. That is to say, if we looked at all countries in the world and plotted suicide rates in a specific year against per capita consumption of bottled water, the plot would show no pattern at all.

两个指标之间的相关系数介于-1和1之间,它衡量的是它们共同影响因素的相对权重。例如,瓶装水消费量和自杀率这类共同影响因素较少的现象,其相关系数应该接近于0。也就是说,如果我们观察世界各国,并将某一年的人均瓶装水消费量与自杀率绘制成图表,那么图表将完全看不出任何规律。

No Correlation

无相关性

Perfect Correlation

完美相关性

By contrast, there are measures that are solely dependent on the same factor. A good example of this is temperature. The only factor governing temperature—velocity of molecules—is shared by all scales. Thus, each degree in Celsius will have exactly one corresponding value in Fahrenheit. Therefore, temperature in Celsius and Fahrenheit will have a correlation coefficient of 1, and the plot will be a straight line.

相比之下,有些测量指标完全取决于同一个因素。温度就是一个很好的例子。影响温度的唯一因素——分子运动速度——是所有温度标度共有的。因此,摄氏度的每一度都恰好对应华氏度的一个值。所以,摄氏度和华氏度之间的相关系数为1,它们之间的关系图将是一条直线。

Perfect Correlation

完美相关性

Weak to Moderate Correlation

弱至中等相关性

There are few phenomena in human sciences that have a correlation coefficient of 1. There are, however, plenty where the association is weak to moderate, and there is some explanatory power between the two phenomena. Consider the correlation between height and weight, which would land somewhere between 0 and 1. While virtually every three-year-old will be lighter and shorter than every grown man, not all grown men or three-year-olds of the same height will weigh the same.

在人类科学领域,相关系数为1的现象寥寥无几。然而,许多现象之间的关联性较弱或中等,且两者之间仍具有一定的解释力。例如,身高和体重之间的相关性就介于0和1之间。虽然几乎所有三岁儿童的身高和体重都低于成年男性,但并非所有身高相同的成年男性或三岁儿童的体重都相同。

Weak to Moderate Correlation

弱至中等相关性

This variation, and the corresponding lower degree of correlation, implies that, while height is a good predictor of weight, there clearly are factors other than height at play.

这种差异以及相应的较低相关程度表明,虽然身高是体重的一个很好的预测指标,但显然除了身高之外还有其他因素在起作用。

In addition, correlation can sometimes work in reverse. Let’s say you read a study that compares alcohol consumption rates in parents and their children’s corresponding academic success. The study shows a relationship between high alcohol consumption and low academic success. Is this causation or correlation? It might be tempting to conclude there’s causality, such as the more parents drink, the worse their kids do in school.

此外,相关性有时也可能是反向的。假设你读到一项研究,该研究比较了父母的饮酒量与其子女相应的学业成绩。研究表明,饮酒量高与学业成绩差之间存在关联。这究竟是因果关系还是相关性呢?人们很容易得出因果关系的结论,例如父母饮酒越多,他们的孩子在学校的表现就越差。

However, this study has demonstrated only a relationship , not proved that one causes the other. The factors correlate—meaning that alcohol consumption in parents has an inverse relationship with academic success in children. It is entirely possible that having parents who consume a lot of alcohol leads to worse academic outcomes for children. It is also possible, however, that the reverse is true, or even that having kids who do poorly in school causes parents to drink more. Trying to invert the relationship can help you sort through claims to determine if you are dealing with true causation or just correlation.

然而,这项研究仅仅表明了二者之间的关系,并未证明二者之间存在因果关系。这些因素之间存在相关性——也就是说,父母饮酒与子女学业成绩呈负相关。父母大量饮酒完全有可能导致子女学业成绩更差。然而,反过来也可能成立,甚至子女学业成绩差也可能导致父母饮酒更多。尝试反向推演这种关系有助于我们筛选各种说法,从而判断我们面对的是真正的因果关系还是仅仅是相关性。

Causation

因果关系

Whenever correlation is imperfect, extremes will soften over time. The best will always appear to get worse, and the worst will appear to get better, regardless of any additional action. This is called regression to the mean, and it means we have to be extra careful when diagnosing causation. This is something that the general media, and sometimes even trained scientists, fail to recognize.

当相关性不完美时,极端情况会随着时间的推移而减弱。最好的情况总是会显得变差,最差的情况也会显得变好,无论采取任何额外措施。这被称为均值回归,这意味着我们在诊断因果关系时必须格外谨慎。这一点常常被大众媒体,甚至一些受过专业训练的科学家所忽视。

Consider the example Daniel Kahneman gives in Thinking, Fast and Slow : [7]

以丹尼尔·卡尼曼在《思考,快与慢》中给出的例子为例:[7]

Depressed children treated with an energy drink improve significantly over a three-month period. I made up this newspaper headline, but the fact it reports is true: if you treated a group of depressed children for some time with an energy drink, they would show a clinically significant improvement. It is also the case that depressed children who spend some time standing on their head or hug a cat for twenty minutes a day will also show improvement.

服用能量饮料治疗的抑郁症儿童在三个月内病情显著改善。这条新闻标题是我编的,但它所报道的事实是真的:如果用能量饮料治疗一群抑郁症儿童一段时间,他们的病情就会出现临床意义上的显著改善。同样,每天花些时间倒立或拥抱猫咪二十分钟的抑郁症儿童也会有所改善。

Whenever we come across such headlines, it is very tempting to jump to the conclusion that energy drinks, standing on the head, or hugging cats are all perfectly viable cures for depression. These cases, however, once again embody the concept of regression to the mean:

每当我们看到这类新闻标题时,很容易会得出这样的结论:能量饮料、倒立或拥抱猫咪都是治疗抑郁症的有效方法。然而,这些案例再次印证了均值回归的概念:

Depressed children are an extreme group—they are more depressed than most other children—and extreme groups regress to the mean over time. The correlation between depression scores on successive occasions of testing is less than perfect, so there will be regression to the mean: depressed children will get somewhat better over time even if they hug no cats and drink no Red Bull.

抑郁儿童是一个极端群体——他们比大多数其他儿童更加抑郁——而极端群体随着时间的推移会回归平均值。连续几次测试中抑郁评分的相关性并不完美,因此会出现均值回归现象:即使抑郁儿童不抱猫也不喝红牛,他们的病情也会随着时间的推移而有所好转。

We often mistakenly attribute a specific policy or treatment as the cause of an effect, when the change in the extreme groups would have happened anyway. This presents a fundamental problem: How can we know if the effect is real or simply due to variability?

我们常常错误地将某种特定政策或措施归因于某种结果的原因,而实际上极端群体的变化无论如何都会发生。这就引出了一个根本性问题:我们如何判断这种结果究竟是真实存在的,还是仅仅是由于个体差异造成的?

Luckily, there is a way to tell between a real improvement and something that would have happened anyway. That is the introduction of the so-called “control group,” which is expected to improve by regression alone. The aim of the research is to determine whether the treated group improves more than regression can explain.

幸运的是,有一种方法可以区分真正的改善和原本就会发生的改变。那就是引入所谓的“对照组”,该组预期仅通过回归分析就能取得改善。这项研究的目的是确定实验组的改善是否超过了回归分析所能解释的范围。

In real-life situations assessing the performance of specific individuals or teams, where the only real benchmark is past performance and no control group can be introduced, the effects of regression can be difficult, if not impossible, to disentangle. We can compare against industry average, peers in the cohort group, or historical rates of improvement, but none of these is a perfect measure.

在实际评估特定个人或团队绩效时,如果唯一的真正基准是过往表现,且无法引入对照组,那么回归效应的影响可能难以消除,甚至根本无法消除。我们可以与行业平均水平、同龄人或历史进步率进行比较,但这些都不是完美的衡量标准。

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Inversion

倒置

Change your perspective.

换个角度看问题。

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The test of a first-rate intelligence is the ability to hold two opposing ideas in mind at the same time and still retain the ability to function. One should, for example, be able to see that things are hopeless yet be determined to make them otherwise.

—F. Scott Fitzgerald [1]

一流智力的标志是能够同时容纳两种对立的观点,并且仍然能够正常思考和行动。例如,一个人应该能够看到事情毫无希望,但仍然决心改变现状。——F·斯科特·菲茨杰拉德[1]
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It can be difficult to appreciate just how much avoiding the standard ways of failing dramatically increases the odds of success.

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人们可能很难意识到,避免常见的失败方式会大大提高成功的几率。

Inversion is all about identifying and removing the obstacles to success. The root of inversion is “invert,” which means to upend or turn upside down. As a thinking tool, it means approaching a situation from the opposite end of the natural starting point.

反转思维的核心在于识别并消除成功路上的障碍。“反转”一词源于“invert”,意为颠倒或翻转。作为一种思维工具,它意味着从与自然起点相反的角度来审视问题。

Most of us tend to think one way about a problem: forward. Inversion allows us to flip the problem around and think backward. Sometimes it’s good to start at the beginning, but it can be more useful to start at the end.

我们大多数人看待问题时倾向于一种方式:向前思考。而逆向思维则允许我们反过来思考问题,从后往前推导。有时从头开始固然不错,但从尾声入手可能更有用。

Avoiding stupidity is easier than seeking brilliance. Even when we don’t know how to achieve a particular objective, we can often identify what prevents it from happening. Perhaps you don’t know all the things that create a good night’s sleep. We can invert the problem by identifying some of the standard things that prevent us from getting a good night’s sleep, such as eating right before going to bed or consuming a lot of alcohol. Simply avoiding those two things dramatically improves the quality of our sleep.

避免愚蠢比追求卓越更容易。即使我们不知道如何达成某个目标,通常也能找出阻碍它实现的因素。也许你并不了解所有有助于获得良好睡眠的因素。我们可以反过来思考,找出一些常见的睡眠障碍,例如睡前吃东西或大量饮酒。仅仅避免这两件事就能显著改善睡眠质量。

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There are two approaches to applying inversion in your life:

在生活中运用倒立有两种方法:

  1. Start by assuming that what you’re trying to prove is either true or false, then show what else would have to be true to make that so.

    首先假设你要证明的事情要么是真的,要么是假的,然后说明为了使这个假设成立,还有哪些事情必须为真。

  2. Instead of aiming directly for your goal, think deeply about what to avoid and then see what options are left over.

    不要直接瞄准目标,而是深入思考应该避免什么,然后再看看还剩下哪些选择。

Set your assumptions: The nineteenth-century German mathematician Carl Jacobi became famous for several reasons—including solving some incredibly difficult problems—but is perhaps best remembered for his advice to “invert, always invert.” [3]

设定你的假设:十九世纪德国数学家卡尔·雅可比因多种原因而闻名——包括解决了一些极其困难的问题——但他最令人难忘的建议或许是“反转,总是反转”。[3]

Jacobi solved a range of problems by starting with the endpoint. When faced with proving an axiom in a difficult math problem, he might instead assume that a property of the axiom was correct and then try to determine the consequences of this assumption. From that point, he could work out surprising, and at times counterintuitive, insights.

雅可比解决一系列问题的方法就是从终点出发。当面对一个棘手的数学问题,需要证明某个公理时,他可能会先假设该公理的某个性质是正确的,然后再尝试推导出这个假设的推论。从这一点出发,他往往能得出一些令人惊讶,有时甚至是违反直觉的见解。

Jacobi was not the first mathematician to use inversion. In fact, inversion is a staple of mathematical, philosophical, and scientific inquiry. We can look around today and appreciate that we can’t see atoms and quarks, but we know they exist because we can make predictions about their behavior and test those predictions.

雅可比并非第一个运用反演的数学家。事实上,反演是数学、哲学和科学探究中不可或缺的工具。我们今天环顾四周,虽然无法直接看到原子和夸克,但我们知道它们的存在,因为我们可以预测它们的行为并检验这些预测。

Or, we can go back 2,300 years and look at the work of the Greek mathematician Hippasus, a follower of Pythagoras. [4] (Yes, the one with the theorem.) His attempts to derive the square root of two, and his original direct approach to solving the problem (essentially, dividing larger and larger whole numbers into each other) were both fruitless and time consuming. He hit an impasse, realizing that he’d never be able to definitely solve the problem by thinking forward. In his increasing frustration, Hippasus decided to take the reverse route, thinking about what the square root of two might imply , and working backward from there. If he couldn’t find it the way he had expected to, he’d start by proving what the number couldn’t be. His quest forever changed what we understood about mathematics and led to the discovery of the first irrational number.

或者,我们可以回到2300年前,看看希腊数学家希帕索斯(毕达哥拉斯的追随者)的工作。[4](没错,就是那个提出毕达哥拉斯定理的数学家。)他试图推导出2的平方根,最初他采用的直接方法(本质上就是将越来越大的整数相除)既徒劳又耗时。他陷入了僵局,意识到自己永远无法通过正向思考来彻底解决这个问题。在日益沮丧中,希帕索斯决定反其道而行之,思考2的平方根可能意味着什么,然后从那里反向推导。如果他无法用预期的方法找到答案,他就先证明这个数不可能是什么。他的探索永远地改变了我们对数学的理解,并最终发现了第一个无理数。

Mathematics is not the only area where using inversion can produce surprising and nonintuitive results. In the 1920s, the American Tobacco Company wanted to sell more of their Lucky Strike cigarettes to women. Men were smoking, but women weren’t. There were pervasive taboos against women smoking—it was seen as a man’s activity. Women, therefore, presented an untapped market that had the potential to provide huge revenue. Riding on the slimness trend that had already begun, the head of the company thought that they needed to convince women that smoking would make them thinner, so he hired Edward Bernays, who came up with a truly revolutionary marketing campaign. [5] , [6]

数学并非唯一一个利用反演能产生令人惊讶且出乎意料的结果的领域。20世纪20年代,美国烟草公司希望向女性消费者销售更多“好彩”(Lucky Strike)香烟。当时男性吸烟,但女性却不吸烟。女性吸烟被视为男性的专属行为,社会上普遍存在着禁忌。因此,女性市场是一个尚未开发的市场,蕴藏着巨大的盈利潜力。鉴于当时流行的苗条身材风潮,公司负责人认为他们需要让女性相信吸烟能使她们更苗条,于是他聘请了爱德华·伯内斯(Edward Bernays),后者策划了一场真正具有革命性的营销活动。[5],[6]

In the style of the inversion approach described above, Bernays did not ask, “How do I sell more cigarettes to women?” Instead, he wondered, if women bought and smoked cigarettes, what else would have to be true? What would have to change in the world to make smoking desirable to women and socially acceptable? Then—a step further—once he knew what needed to change, how would he achieve that?

按照上文所述的反向思维方式,伯内斯并没有问:“我该如何向女性销售更多香烟?”相反,他思考的是,如果女性购买并吸烟,那么还有哪些条件必须成立?世界需要发生哪些改变才能使吸烟对女性具有吸引力并被社会接受?然后——更进一步——一旦他知道需要改变什么,他该如何实现这些改变?

To tackle the idea of smoking as a slimming aid, Bernays mounted a large anti-sweets campaign. After dinner, it was all about cigarettes, not dessert. Cigarettes were slimming, while desserts would ruin one’s figure. But Bernays’s real stroke of genius did lie solely in coming out with advertisements to convince women to stay slim by smoking cigarettes. As author Alan Axelrod puts it, “Instead, he sought nothing less than to reshape American society and culture.” [7] He solicited journalists and photographers to promote the virtues of being slim. He sought testimonials from doctors about the health value of smoking after a meal. He combined this approach with “altering the very environment, striving to create a world in which the cigarette was ubiquitous.” Axelrod details the full scope of Bernays’s efforts:

为了驳斥吸烟减肥的说法,伯内斯发起了一场声势浩大的反甜食运动。晚餐后,人们的关注点不再是甜点,而是香烟。香烟被认为可以减肥,而甜点则会破坏身材。但伯内斯真正的天才之处在于,他推出了一系列广告,说服女性通过吸烟来保持苗条身材。正如作家艾伦·阿克塞尔罗德所说,“他追求的远不止于此,而是重塑美国社会和文化。”[7] 他招募记者和摄影师来宣传苗条的好处。他还向医生征集餐后吸烟有益健康的证词。此外,他还“改变环境,力图创造一个香烟无处不在的世界”。阿克塞尔罗德详细描述了伯内斯的全部努力:

He mounted a campaign to persuade hotels and restaurants to add cigarettes to dessert-list menus, and he provided such magazines as House and Garden with feature articles that included menus designed to preserve readers “from the dangers of overeating.”…The idea was not only to influence opinion but to remold life itself. Bernays approached designers, architects, and cabinetmakers in an effort to persuade them to design kitchen cabinets that included special compartments for cigarettes, and he spoke to the manufacturers of kitchen containers to add cigarette tins to their traditional lines of labeled containers for coffee, tea, sugar, and flour. [8]

他发起了一场运动,说服酒店和餐馆在甜点菜单上添加香烟,并向《家居与花园》等杂志提供专题文章,其中包含旨在帮助读者“避免暴饮暴食”的菜单设计……其目的不仅在于影响舆论,更在于重塑生活本身。伯内斯与设计师、建筑师和橱柜制造商接洽,试图说服他们在厨房橱柜中设计专门放置香烟的隔间;他还与厨房容器制造商洽谈,希望他们在传统的咖啡、茶、糖和面粉等标签容器系列中增加香烟罐。[8]

The result was a complete shift in the consumption habits of American women. It wasn’t just about selling the cigarette; it was about reorganizing society to make cigarettes an inescapable part of the American woman’s daily experience.

其结果是美国女性的消费习惯发生了彻底的转变。这不仅仅是卖香烟的问题;而是要重组社会,使香烟成为美国女性日常生活中不可或缺的一部分。

Bernays’s efforts to make women’s smoking in public socially acceptable had equally startling results. He linked cigarette smoking with women’s emancipation: to smoke was to be free. Cigarettes were marketed as “torches of freedom.” He orchestrated public events, including an infamous parade on Easter Sunday in 1929, which featured women smoking as they walked in the parade. He left no detail unattended, so that public perception of smoking was changed almost overnight. He both normalized it and made it desirable in one swoop.

伯内斯为使女性在公共场合吸烟被社会接受所做的努力,同样取得了惊人的成果。他将吸烟与女性解放联系起来:吸烟就意味着自由。香烟被宣传为“自由之火”。他精心策划了一系列公共活动,其中包括1929年复活节星期日那场臭名昭著的游行,游行队伍中女性一边吸烟一边行进。他事无巨细,几乎一夜之间就改变了公众对吸烟的看法。他一举将吸烟正常化,并使其变得令人向往。

Although the Lucky Strike campaign utilized more principles than just inversion, it was the original decision to invert the approach that provided the framework from which the campaign was created and executed. Bernays didn’t focus on how to sell more cigarettes to women within the existing social structure. If he had, undoubtedly sales would have been a lot more limited. Instead, he thought about what the world would look like if women smoked often and anywhere, and then set about trying to make that world a reality. Once he did that, selling cigarettes to women was comparatively easy.

尽管好彩香烟的营销活动运用了不止一种反转策略,但正是最初反转策略的决定,为整个活动的创建和执行奠定了基础。伯内斯并没有专注于如何在现有的社会结构下向女性销售更多香烟。如果他那样做,销量无疑会受到很大限制。相反,他设想如果女性随时随地都能吸烟,世界将会变成什么样子,然后着手将这种设想变为现实。一旦他做到了这一点,向女性销售香烟就相对容易了。

This inversion approach became a staple of Bernays’s work. He used the descriptor “appeals of indirection,” and each time he was hired to sell a product or service, “he instead sold whole new ways of behaving, which appeared obscure but over time reaped huge rewards for his clients and redefined the very texture of American life.” [9]

这种反其道而行之的方法成为伯内斯作品的一大特色。他使用了“间接诉求”这一描述,每次受雇推销产品或服务时,“他都会推销全新的行为方式,这些方式看似晦涩难懂,但随着时间的推移,却为他的客户带来了巨大的回报,并重新定义了美国人的生活面貌。”[9]

Decide what to avoid: Instead of thinking through the achievement of a positive outcome, another way to use inversion is to ask ourselves how we might achieve a terrible outcome, and let that guide our decision making.

决定要避免什么:与其思考如何取得积极的结果,不如反过来思考如何取得糟糕的结果,并以此指导我们的决策。

Index funds are a great example of stock market inversion, promoted and brought to bear by Vanguard’s John Bogle. [10] Instead of asking how to beat the market, as so many before him had, Bogle simply recognized the difficulty of the task. Everyone is trying to beat the market. No one is doing it with any consistency, and in the process real people are losing actual money. So Bogle inverted the approach. The question then became, how can we help investors minimize losses to fees and poor money manager selection? The results were one of the greatest ideas—index funds—and one of the greatest powerhouse firms in the history of finance.

指数基金是股市反向操作的绝佳例证,由先锋集团的约翰·博格尔推广并实施。[10] 与之前许多人探讨如何战胜市场不同,博格尔只是认识到这项任务的难度。每个人都试图战胜市场,但没有人能够持续做到,在这个过程中,人们确实在蒙受损失。因此,博格尔反其道而行之。问题变成了:我们如何帮助投资者最大限度地减少因费用和糟糕的基金经理选择而造成的损失?最终的成果是:指数基金——这一最伟大的理念之一——以及金融史上最强大的公司之一。

Index funds operate on the idea that accruing wealth has a lot to do with minimizing loss. Think about your personal finances: Often, we focus on positive goals, such as “I want to be rich,” and use this to guide our approach. We make investing and career choices based on our desire to accumulate wealth. We chase after magical solutions, like attempting to outsmart the stock market. These inevitably get us nowhere, and we have usually taken some terrible risks in the process that leave us worse off.

指数基金的运作理念是,财富积累的关键在于尽可能减少损失。想想你的个人财务状况:我们常常专注于积极的目标,比如“我想变得富有”,并以此指导我们的理财方式。我们基于积累财富的愿望做出投资和职业选择。我们追求神奇的解决方案,比如试图战胜股市。但这些最终都以失败告终,而且在这个过程中,我们通常会承担一些可怕的风险,最终反而让自己更加窘迫。

Inverting our approach, we can instead ask ourselves what the common pitfalls in investing are and how we can avoid them. For example, spending more than we make, taking on too much leverage (or paying high interest rates on debt so that we can’t tackle paying back the principal), and not starting to save as early as we can so as to take advantage of the power of compounding are all concrete financial behaviors that cost us money. We can more readily secure wealth by using inversion to make sure we are not doing the worst things that prevent the accumulation of wealth.

反过来,我们可以问问自己投资中常见的陷阱有哪些,以及如何避免它们。例如,入不敷出、过度杠杆(或支付高额利息导致无力偿还本金)、以及未能尽早开始储蓄以利用复利效应,这些都是会让我们损失金钱的实际财务行为。通过反向思考,确保自己避免那些阻碍财富积累的“罪魁祸首”,我们就能更轻松地保障财富安全。

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One of the theoretical foundations for this type of thinking comes from psychologist Kurt Lewin. [12] In the 1930s, he came up with the idea of “force field analysis,” which essentially recognizes that in any situation where change is desired, successful management of that change requires applied inversion. Here is a brief explanation of his process:

这种思维方式的理论基础之一来自心理学家库尔特·勒温。[12] 20世纪30年代,他提出了“力场分析”的概念,其核心观点是,在任何需要变革的情况下,成功管理变革都需要运用逆向思维。以下是对其过程的简要说明:

  1. Identify the problem.

    找出问题所在。

  2. Define your objective.

    明确你的目标。

  3. Identify the forces that support change toward your objective.

    找出有助于实现目标的变革力量。

  4. Identify the forces that impede change toward the objective.

    找出阻碍实现目标的因素。

  5. Strategize a solution! This may involve both augmenting, or adding to, the forces in step 3 and reducing or eliminating the forces in step 4.

    制定解决方案!这可能包括增强或增加步骤 3 中的作用力,以及减弱或消除步骤 4 中的作用力。

Even if we are quite logical, most of us stop after step 3. Once we figure out our objective, we focus on the things we need to put in place to make it happen—the new training or education, the messaging and marketing. But Lewin theorized that it can be just as powerful to remove obstacles to change.

即使我们逻辑思维很强,大多数人也会止步于第三步。一旦确定了目标,我们就会专注于实现目标所需的具体措施——新的培训或教育、信息传递和市场营销。但勒温认为,消除变革的障碍同样至关重要。

The inversion happens between steps 3 and 4. Whatever angle you choose to approach your problem from, you need to then follow up with consideration of the opposite angle. Think about not only what you could do to solve a problem but what you could do to make it worse—and then avoid doing that, or eliminate the conditions that perpetuate it.

倒置发生在步骤 3 和 4 之间。无论你选择从哪个角度切入问题,都需要考虑其相反的角度。不仅要思考如何解决问题,还要思考如何让问题变得更糟——然后避免这样做,或者消除导致问题持续存在的条件。

This inversion approach was used by Florence Nightingale to help significantly reduce the mortality rate of British soldiers in military hospitals in the mid-nineteenth century. Nightingale is often remembered as the founder of modern nursing, but she was also an excellent statistician and was the first woman elected to the Royal Statistical Society, in 1858.

弗洛伦斯·南丁格尔运用这种反向方法,在十九世纪中期显著降低了英国军医院士兵的死亡率。南丁格尔常被誉为现代护理学的创始人,但她也是一位杰出的统计学家,并于1858年成为首位当选为英国皇家统计学会会员的女性。

During the first winter of the Crimean War, 1854–55, the British Army endured a death rate of 23 percent. The next winter that rate had dropped to 2.5 percent. [13] The main reason for the change was a much better understanding of what was actually killing the soldiers, an understanding that rested on the detailed statistics that Florence Nightingale collected. She demonstrated that the leading cause of death by far was poor sanitation. In her famous polar-area chart—a completely new way of presenting data at the time—she captured a visual representation of the statistics that made them easy to understand. Improve the sanitary conditions in the hospitals, she explained, and many soldiers’ lives would be saved.

在克里米亚战争的第一个冬天(1854-1855年),英军的死亡率高达23%。到了第二个冬天,死亡率骤降至2.5%。[13] 这一转变的主要原因是人们对士兵死亡的真正原因有了更深入的了解,而这种了解又得益于弗洛伦斯·南丁格尔收集的详细统计数据。她证明,造成士兵死亡的首要原因是恶劣的卫生条件。在她著名的极坐标图——一种在当时全新的数据呈现方式——中,她以可视化的方式呈现了这些统计数据,使其易于理解。她解释说,改善医院的卫生条件,就能挽救许多士兵的生命。

Nightingale’s use of statistics helped to identify the real problem of army-hospital deaths. She was able to demonstrate not only what the army could do to improve outcomes but, just as important, what they had to avoid doing to stop making things worse. She reflected on the knowledge that could be derived from statistics and, in another instance of inversion thinking, she advocated for their use as a means of prevention. [14] The question became not so much “how do we fix this problem?” but “how do we stop it from happening in the first place?” Nightingale took the knowledge and experience she gained in Crimea and began gathering statistics not just for British Army field hospitals but for domestic ones as well. She demonstrated that unsanitary conditions in military hospitals were a real problem causing many preventable deaths. [15]

南丁格尔对统计数据的运用帮助人们认清了军队医院死亡问题的真正根源。她不仅能够证明军队可以采取哪些措施来改善医疗结果,而且同样重要的是,她还指出了军队必须避免哪些做法才能避免情况恶化。她反思了统计数据所能提供的知识,并再次运用逆向思维,倡导将统计数据作为预防手段。[14] 问题不再是“我们如何解决这个问题?”,而是“我们如何从一开始就阻止它的发生?” 南丁格尔运用她在克里米亚获得的知识和经验,开始收集统计数据,不仅包括英国陆军野战医院,也包括国内医院。她证明,军医院不卫生的状况是一个真实存在的问题,导致了许多本可避免的死亡。[15]

Nightingale’s advocacy for statistics ultimately went much further than British military hospitals. But her use of statistics to improve sanitary conditions can be seen as an example of applied inversion. She used them to advocate for both solving problems and the invert, preventing them.

南丁格尔对统计学的倡导最终远远超出了英国军医院的范畴。但她运用统计学改善卫生条件的做法,可以被视为应用逆向思维的一个例证。她既利用统计学来解决问题,也利用统计学来预防问题的发生。

Hence to fight and conquer in all your battles is not supreme excellence; supreme excellence consists in breaking the enemy’s resistance without fighting.

—Sun Tzu [16]

因此,在所有战斗中都取得胜利并非最高境界;最高境界在于不战而屈人之兵。——孙子[16]

Conclusion

结论

A lot of advantage is gained simply by avoiding the standard paths to failure.

避免走常见的失败之路,就能获得很多优势。

Inversion is not the way we are taught to think. We are taught to identify what we want and explore things that will move us closer to our objective. However, by spending time identifying things that will ensure we don’t get what we want, we dramatically increase our odds of success.

逆向思维并非我们通常被教导的思考方式。我们被教导要先明确自己想要什么,然后探索那些能帮助我们更接近目标的途径。然而,如果我们花时间去识别那些会阻碍我们达成目标的因素,就能显著提高成功的几率。

Often, we get so fixated on solving a problem in a particular way that we miss simpler, more elegant solutions. Inversion forces us to consider the opposite side of the equation.

我们常常过于执着于用某种特定方法解决问题,反而忽略了更简单、更优雅的方案。而逆向思维则迫使我们考虑等式的另一边。

Instead of asking, “How do I solve this problem?” inversion asks, “What would guarantee failure?” Instead of asking, “How can I achieve this goal?” it asks, “What is preventing me from achieving it?” By inverting the question, we can gain insights that our normal thought patterns might miss.

与其问“我该如何解决这个问题?”,不如反过来问“什么因素必然会导致失败?”;与其问“我该如何实现这个目标?”,不如反过来问“是什么阻碍了我实现这个目标?”。通过反过来问,我们可以获得一些我们通常思维模式可能忽略的洞见。

The next time you’re grappling with a difficult problem or striving toward an ambitious goal, try inverting your thinking. Ask yourself how you could guarantee failure. The answers may surprise you and open up new avenues for possible solutions.

下次当你遇到难题或努力实现远大目标时,不妨换个角度思考。问问自己,怎样才能确保失败?答案或许会让你大吃一惊,并为找到新的解决方案开辟道路。

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Occam’s Razor

奥卡姆剃刀

Keep it simple.

保持简单。

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Anybody can make the simple complicated. Creativity is making the complicated simple.

—Charles Mingus [1]

任何人都能把简单的事情复杂化。创造力就是化繁为简。——查尔斯·明格斯[1]
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Simpler explanations are more likely to be true than complicated ones. This is the essence of Occam’s razor, a classic principle of logic and problem solving. Instead of wasting your time trying to disprove complex scenarios, you can make decisions more confidently by basing them on the explanation that has the fewest moving parts.

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简单的解释往往比复杂的解释更可能是正确的。这就是奥卡姆剃刀原理的精髓所在,它是逻辑和问题解决领域的经典原则。与其浪费时间试图反驳复杂的场景,不如基于最少复杂因素的解释做出更有信心的决策。

The more complicated the explanation for something, the more skeptical you should be.

对某件事的解释越复杂,你就越应该持怀疑态度。

We all jump to overly complex explanations about something. Husband late getting home? What if he’s been in a car accident? Son grew a centimeter less than he did last year? What if there’s something wrong with him? Your toe hurts? What if you have bone cancer? Although it is possible that any of these worst-case scenarios could be true, without any other correlating factors, it is significantly more likely that your husband got caught up at work, you mismeasured your son, and your shoe is too tight.

我们总是习惯性地对一些事情进行过于复杂的解释。丈夫回家晚了?万一他出了车祸呢?儿子比去年少长了一厘米?万一他身体不舒服呢?脚趾头疼?万一你得了骨癌呢?虽然这些最糟糕的情况都有可能发生,但如果没有其他相关因素,更有可能的情况是:你丈夫工作太忙,你没量好儿子的身高,或者你的鞋子太紧了。

We often spend lots of time coming up with very complicated narratives to explain what we see around us. From the behavior of people on the street to physical phenomena, we get caught up in assuming vast icebergs of meaning beyond the tips that we observe. This is a common human tendency, and it serves us well in some situations, such as creating art. However, complexity takes work to unravel, manage, and understand.

我们常常花费大量时间构建极其复杂的叙事来解释我们周围的一切。从街头行人的行为到自然现象,我们总是倾向于假设冰山之下隐藏着远超我们观察到的表象的巨大意义。这是一种常见的人类倾向,在某些情况下,例如艺术创作,它对我们大有裨益。然而,要解开、驾驭和理解复杂性,需要付出努力。

Occam’s razor is a great tool for avoiding unnecessary complexity by helping you identify and commit to the simplest explanation possible.

奥卡姆剃刀原理是一个很好的工具,它能帮助你找到并坚持使用最简单的解释,从而避免不必要的复杂性。

Named after the medieval logician William of Ockham, Occam’s razor is a general rule by which we select among competing explanations. Ockham wrote that “a plurality is not to be posited without necessity”—essentially, that we should prefer the simplest explanation with the fewest moving parts. [2] , [3] Simple explanations are easier to falsify, easier to understand, and generally more likely to be correct. Occam’s razor is not an iron law but a tendency and a mindset you can choose to use: if all else is equal—that is, if two competing models both have equal explanatory power—it’s more likely that the simple solution suffices.

奥卡姆剃刀原理以中世纪逻辑学家威廉·奥卡姆的名字命名,是一条用于在相互竞争的解释中进行选择的通用规则。奥卡姆写道:“不应无故假设多种解释”——本质上,我们应该优先选择最简单、最少复杂因素的解释。[2],[3] 简单的解释更容易证伪,更容易理解,而且通常也更可能是正确的。奥卡姆剃刀原理并非铁律,而是一种倾向和思维方式,你可以选择运用它:在其他条件相同的情况下——也就是说,如果两个相互竞争的模型具有相同的解释力——那么简单的解决方案更有可能足够。

Ockham himself did not derive this idea, which had been in use since antiquity. Nor was Ockham the last to note the value of simplicity. The principle was stated in another useful way by the eighteenth-century Scottish philosopher David Hume, in his famous Enquiry Concerning Human Understanding. Writing about the truth or untruth of miracles, Hume stated that we should default to skepticism about them. [4]

奥卡姆本人并非这一思想的原创者,这一思想自古以来就已存在。奥卡姆也不是最后一个注意到简洁价值的人。十八世纪苏格兰哲学家大卫·休谟在其著名的《人类理解研究》中,以另一种有益的方式阐述了这一原则。休谟在论述奇迹的真伪时指出,我们应该默认对奇迹持怀疑态度。[4]

Why? It wasn’t simply that Hume was a buzzkill. He had a specific, Occam-like reason for being cautious about miracles. By definition, a miracle is something that has happened outside of our normal understanding of the way nature works. If the miracle was not outside of our common experience, we wouldn’t consider its occurrence miraculous. If there was a simple explanation for the occurrence based on mostly common knowledge, we likely wouldn’t pay much attention to it at all.

为什么?并非休谟只是个扫兴的人。他对奇迹持谨慎态度,有着类似奥卡姆推理的特定理由。根据定义,奇迹是指发生在我们通常对自然运行方式的理解之外的事件。如果奇迹并非超出我们的日常经验,我们就不会认为它的发生是奇迹。如果奇迹的发生可以用基于常识的简单解释来解释,我们很可能根本不会关注它。

Therefore, the simplest explanation for a miracle is that the miracle witnesser is not describing the event correctly, or the miracle represents a more common phenomenon that we currently don’t properly understand. As scientist and writer Carl Sagan explains in The Demon-Haunted World :

因此,对奇迹最简单的解释是,奇迹的目击者没有正确描述事件,或者奇迹代表了一种我们目前尚未充分理解的更常见的现象。正如科学家兼作家卡尔·萨根在《魔鬼出没的世界》中所解释的那样:

A multitude of aspects of the natural world that were considered miraculous only a few generations ago are now thoroughly understood in terms of physics and chemistry. At least some of the mysteries of today will be comprehensively solved by our descendants. The fact that we cannot now produce a detailed understanding of, say, altered states of consciousness in terms of brain chemistry no more implies the existence of a “spirit world” than a sunflower following the Sun in its course across the sky was evidence of a literal miracle before we knew about phototropism and plant hormones. [5]

几代人之前还被认为是奇迹的自然界诸多方面,如今已能用物理学和化学的原理彻底理解。至少当今的一些谜团,终将被我们的后代彻底解开。我们现在无法从脑化学的角度详细理解意识状态的改变,但这并不能证明“精神世界”的存在,正如在我们知道向光性和植物激素之前,向日葵追随太阳在天空中旋转并不能证明这是一个真正的奇迹一样。[5]

The simpler explanation for a miracle is that there are principles of nature being exploited that we do not understand. This is Hume’s and Sagan’s point.

对奇迹更简单的解释是,自然界存在我们尚未理解的规律并被运用其中。这正是休谟和萨根的观点。

Dark What?

黑暗的什么?

In the mid-1970s, astronomer Vera Rubin had a very interesting problem. She had a bunch of data piling up about the behavior of galaxies that wasn’t explained by contemporary theories. [6] , [7] , [8]

20 世纪 70 年代中期,天文学家维拉·鲁宾遇到了一个非常有趣的问题。她积累了大量关于星系行为的数据,但当时的理论无法解释这些数据。[6],[7],[8]

Rubin had been observing the behavior of the Andromeda Galaxy and had noticed something very strange. As explained in an article on Astronomy.com, “The vast spiral seemed to be rotating all wrong. The stuff at the edges was moving just as fast as the stuff near the center, apparently violating Newton’s laws of motion (which also govern how the planets move around our Sun).” [9] This didn’t make any sense. Gravity should exert less pull on distant objects, which should move slower. But Rubin was observing something entirely different.

鲁宾一直在观察仙女座星系的运行轨迹,并注意到了一些非常奇怪的现象。正如Astronomy.com网站上的一篇文章所解释的那样,“这个巨大的螺旋星系似乎旋转得完全不对劲。边缘的物质运动速度与中心附近的物质一样快,这显然违反了牛顿运动定律(该定律也适用于行星绕太阳运行)。”[9] 这完全不合常理。引力对遥远物体的作用力应该较小,因此它们的运动速度应该更慢。但鲁宾观察到的却是完全不同的现象。

One possible explanation was something that had been theorized as far back as 1933, by Swiss astrophysicist Fritz Zwicky, who coined the phrase “dark matter” to describe a mass we couldn’t see but that was influencing the behavior of orbits in the galaxies. Dark matter became the simplest explanation for the observed phenomenon, and Vera Rubin has been credited with providing the first evidence of its existence. What is particularly interesting is that, to this day, no one has ever actually discovered dark matter.

一种可能的解释是瑞士天体物理学家弗里茨·兹威基早在1933年就提出的理论。他创造了“暗物质”一词,用来描述一种我们无法直接观测到,但却影响着星系轨道运动的物质。暗物质成为对观测到的现象最简单的解释,而维拉·鲁宾被认为是第一个提供暗物质存在证据的人。尤其令人感兴趣的是,时至今日,仍然没有人真正发现过暗物质。

Why are more complicated explanations less likely to be true? Let’s work it out mathematically. Take two competing explanations, each of which seems equally to explain a given phenomenon. If one of them requires the interaction of three variables, and the other the interaction of thirty variables—all of which must have occurred to arrive at the stated conclusion—which of these is more likely to be in error? If each variable has a 99 percent chance of being correct, the first explanation is only 3 percent likely to be wrong. The second, more complex explanation, is about nine times as likely to be wrong, or 26 percent. The simpler explanation is more robust in the face of uncertainty.

为什么更复杂的解释更不可能是正确的?让我们用数学方法来分析。假设有两种相互竞争的解释,它们似乎都能同样有效地解释某个现象。如果其中一种解释需要三个变量的相互作用,而另一种解释需要三十个变量的相互作用——所有这些变量都必须同时存在才能得出既定的结论——那么哪一种解释更可能出错?如果每个变量的正确概率都是99%,那么第一种解释出错的概率只有3%。第二种解释,也就是更复杂的解释,出错的概率大约是第一种的九倍,也就是26%。面对不确定性,更简单的解释反而更可靠。

Dark matter is an excellent theory with a lot of explanatory power. As Lisa Randall explains in Dark Matter and the Dinosaurs , measurements of dark matter so far fit in exactly with what we understand about the universe. Although we can’t see it, we can make predictions based on our understanding of it and test those predictions. Randall writes, “It would be even more mysterious to me if the matter we can see with our eyes is all the matter that exists.” [10] Dark matter is currently the simplest explanation for certain phenomena we observe in the universe. The great thing about science, however, is that it continually seeks to validate its assumptions.

暗物质是一个极佳的理论,具有强大的解释力。正如丽莎·兰德尔在《暗物质与恐龙》一书中解释的那样,迄今为止对暗物质的测量结果与我们对宇宙的理解完全吻合。虽然我们无法直接观测到它,但我们可以根据对它的理解做出预测,并检验这些预测。兰德尔写道:“如果我们肉眼可见的物质就是宇宙中存在的全部物质,那对我来说将更加神秘。”[10] 暗物质目前是对我们观测到的某些宇宙现象最简单的解释。然而,科学的伟大之处在于,它不断地寻求验证自身的假设。

Carl Sagan wrote that “extraordinary claims require extraordinary proof.” [11] He dedicated much ink to rational investigation of extraordinary claims. He felt most, or nearly all, were susceptible to simpler and more parsimonious explanations. UFOs, paranormal activity, telepathy, and a hundred other seemingly mystifying occurrences could be better explained by the confluence of a few simple real-world variables—and, as Hume suggested, if they couldn’t, it was a lot more likely that we needed to update our understanding of the world than that a miracle had occurred.

卡尔·萨根写道:“非凡的断言需要非凡的证据。”[11] 他花费大量笔墨对非凡的断言进行理性探究。他认为大多数,或者说几乎所有断言,都可以用更简单、更精炼的解释来解释。不明飞行物、超自然现象、心灵感应以及其他数百种看似神秘的事件,都可以用几个简单的现实世界变量的汇合来更好地解释——而且,正如休谟所言,如果这些现象无法解释,那么更有可能是我们需要更新对世界的理解,而不是发生了奇迹。

And so, dark matter remains, right now, the simplest explanation for the peculiar behavior of galaxies. Scientists, however, continue to try to conclusively discover dark matter and thus to determine if our understanding of the world is correct. If dark matter eventually becomes too complicated an explanation, it could be that the data describes something we don’t yet understand about the universe. We can then apply Occam’s razor to update what is the simplest, and thus most likely, explanation.

因此,就目前而言,暗物质仍然是解释星系奇特行为的最简单方法。然而,科学家们仍在努力寻找暗物质的确切来源,从而确定我们对世界的理解是否正确。如果暗物质最终变得过于复杂,那么数据可能描述了我们尚未了解的宇宙奥秘。届时,我们可以运用奥卡姆剃刀原理来更新最简单、因而也是最有可能的解释。

Vera Rubin herself, after noting that scientists always felt as though they were ten years away from discovering dark matter, without ever closing the gap, was described by an interviewer as thinking, “The longer that dark matter went undetected…the more likely she thought the solution to the mystery would be a modification to our understanding of gravity.” [12] This claim, demanding a total overhaul of our established theories of gravity, would correspondingly require extraordinary proof!

维拉·鲁宾本人曾指出,科学家们总是感觉离发现暗物质还有十年之遥,却始终未能弥合这一差距。一位采访者描述她当时的想法是:“暗物质被发现的时间越长……她就越认为解开这个谜团的关键在于修正我们对引力的理解。”[12] 这一论断要求彻底推翻我们已有的引力理论,因此也需要非凡的证据!

Simplicity Can Increase Efficiency

化繁为简可以提高效率

With limited time and resources, it is not possible to track down every theory with a plausible explanation of a complex, uncertain event. Without the filter of Occam’s razor, we are stuck chasing down dead ends. We waste time, resources, and energy.

在时间和资源有限的情况下,我们不可能逐一探究所有看似合理的解释,以应对复杂且充满不确定性的事件。如果没有奥卡姆剃刀的过滤,我们只会陷入徒劳的追寻,白白浪费时间、资源和精力。

The great thing about simplicity is that it can be so powerful. Sometimes unnecessary complexity just papers over the systemic flaws that will eventually choke us. Opting for the simple helps us make decisions based on how things really are. Here are two short examples of those who got waylaid chasing down complicated solutions when simple ones were most effective.

简洁的妙处在于它蕴含着强大的力量。有时,不必要的复杂性只会掩盖系统性的缺陷,而这些缺陷最终会让我们窒息。选择简单的方式能帮助我们根据事物的本来面目做出决策。以下两个例子简要说明了为什么有些人因为追求复杂的解决方案而错失良机,而简单的方案才是最有效的。

The ten-acre Ivanhoe Reservoir in Los Angeles provides drinking water for more than six hundred thousand people. Its nearly sixty million gallons of water are disinfected with chlorine, as is common practice. [13] Groundwater often contains elevated levels of a chemical called bromide. When chlorine and bromide mix, then are exposed to sunlight, they create a dangerous carcinogen called bromate.

位于洛杉矶的伊万霍水库占地十英亩,为超过六十万人提供饮用水。按照惯例,其近六千万加仑的水都用氯进行消毒。[13] 地下水中通常含有高浓度的溴化物。氯和溴化物混合后,暴露在阳光下,会产生一种名为溴酸盐的危险致癌物。

To avoid poisoning the water supply, the LA Department of Water and Power (DWP) needed a way to shade the water’s surface. Brainstorming sessions had yielded only two infeasible solutions: building either a ten-acre tarp or a huge retractable dome over the reservoir. Then a DWP biologist suggested using “bird balls,” the floating balls that airports use to keep birds from congregating near runways. They required no construction, no parts, no labor, no maintenance, and cost forty cents each. Three million UV-deflecting black balls were eventually deployed in Ivanhoe and other LA reservoirs, a simple solution to a potentially serious problem.

为了避免污染水源,洛杉矶水电局 (DWP) 需要找到一种方法来遮蔽水面。经过一番头脑风暴,他们只提出了两个不可行方案:要么在水库上方建造一块十英亩的防水布,要么建造一个巨大的可伸缩穹顶。后来,一位 DWP 的生物学家建议使用“防鸟球”,也就是机场用来防止鸟类聚集在跑道附近的漂浮球。这种球无需建造、无需零件、无需人工、无需维护,而且每个成本仅为 40 美分。最终,300 万个能反射紫外线的黑色球被部署在伊万霍水库和其他洛杉矶水库中,一个简单的方案就解决了潜在的严重问题。

In another life-and-death situation, in 1989, Bengal tigers killed about sixty villagers in India’s Ganges Delta. [14] No weapon seemed to work against them, including lacing dummies with live wires to shock the tigers away from attacking human populations.

在另一起生死攸关的事件中,1989 年,孟加拉虎在印度恒河三角洲杀死了约 60 名村民。[14] 似乎没有任何武器能对付它们,包括在假人身上绑上带电的电线来电击老虎,使其远离人类。

Then a student at the Science Club of Calcutta noticed that tigers attacked only when they thought they were unseen and recalled that the patterns decorating some species of butterflies, beetles, and caterpillars look like big eyes, ostensibly to trick predators into thinking their prey is also watching them. The result: a human face mask, worn on the back of the head. Remarkably, no one wearing a mask was attacked by a tiger for the next three years; anyone killed by a tiger during that time either had refused to wear the mask or had taken it off while working.

后来,加尔各答科学俱乐部的一名学生注意到,老虎只有在认为自己没有被发现时才会发动攻击。他想起某些蝴蝶、甲虫和毛虫身上的图案看起来像大眼睛,显然是为了迷惑捕食者,让它们误以为猎物也在注视着自己。于是,他发明了一种戴在后脑勺上的面具。令人惊讶的是,在接下来的三年里,没有一个戴面具的人遭到老虎袭击;那段时间里被老虎杀死的人,要么是拒绝佩戴面具,要么是在工作时摘下了面具。

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A Few Caveats

一些注意事项

One important counter to Occam’s razor is the difficult truth that some things are simply not that simple. The regular recurrence of fraudulent human enterprises like pyramid schemes and Ponzi schemes is not a miracle, but neither is it obvious. No simple explanation suffices, exactly. Such cons are a result of a complex set of behaviors, some happening almost by accident or luck, and some carefully designed with the intent to deceive. It isn’t a bit easy to spot the development of a fraud; if it was, they’d be stamped out early. Yet, to this day, frauds frequently grow to epic proportions before they are discovered.

奥卡姆剃刀原理的一个重要反驳是,有些事情远没有那么简单,这是一个残酷的现实。像传销和庞氏骗局这类诈骗活动屡屡出现并非奇迹,但也并非显而易见。没有简单的解释能够完全说明问题。这类骗局是多种复杂行为共同作用的结果,有些几乎是偶然或运气使然,有些则是精心策划、蓄意欺骗。要发现骗局的萌芽阶段绝非易事;如果容易发现,它们早就被扼杀在萌芽状态了。然而,时至今日,许多骗局在被发现之前,规模仍然可能已经发展到惊人的程度。

Alternatively, consider the achievement of human flight. It too might seem like a miracle to our fourteenth-century friar, but it isn’t—it’s a natural consequence of applied physics. Still, it took a long time for humans to figure out because it’s not simple at all. In fact, the invention of powered human flight is highly counterintuitive, requiring an understanding of airflow, lift, drag, and combustion, among other difficult concepts. Only a precise combination of the right factors will do. You can’t know just enough to get the aircraft off the ground, you need to keep it in the air!

或者,想想人类飞行的成就。对于我们这位十四世纪的修士来说,这或许也像是一个奇迹,但并非如此——它是应用物理学的自然结果。尽管如此,人类还是花了很长时间才弄明白,因为它绝非易事。事实上,动力飞行的发明与直觉非常相悖,它需要理解气流、升力、阻力和燃烧等诸多复杂概念。只有各种因素的精确组合才能成功。你不能只知道让飞机起飞所需的知识,你还需要让它持续飞行!

Simple as we wish things were, irreducible complexity, like simplicity, is a part of our reality. Therefore, we can’t use Occam’s razor to create artificial simplicity. If something cannot be broken down any further, we must deal with it as it is.

尽管我们希望事情简单,但不可简化的复杂性,如同简单本身一样,也是我们现实的一部分。因此,我们不能用奥卡姆剃刀原理人为地制造简单。如果某件事无法进一步分解,我们就必须接受它的本来面目。

How do you know something is as simple as it can be? Think of computer code. Code can sometimes be excessively complex. In trying to simplify it, we would have to make sure it can still perform the functions we need it to. This is one way to understand simplicity: an explanation can be simplified only to the extent that it can still provide an accurate understanding.

如何判断某件事是否已经足够简单?想想计算机代码。代码有时会过于复杂。在尝试简化代码时,我们必须确保它仍然能够执行我们所需的功能。这是理解简洁性的一种方法:解释只有在能够提供准确理解的范围内才能被简化。

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Conclusion

结论

Occam’s razor is the intellectual equivalent of “keep it simple.”

奥卡姆剃刀原理在智力领域相当于“保持简单”。

When faced with competing explanations or solutions, Occam’s razor suggests that the correct explanation is most likely the simplest one, the one that makes the fewest assumptions.

当面临相互竞争的解释或解决方案时,奥卡姆剃刀原理表明,正确的解释很可能是最简单的解释,即假设最少的解释。

This doesn’t mean the simplest theory is always true, only that it should be preferred until proven otherwise. Sometimes, the truth is complex, and the simplest explanation doesn’t account for all the facts.

这并不意味着最简单的理论总是正确的,而只是说在被证明错误之前,应该优先考虑最简单的理论。有时,真相很复杂,最简单的解释无法涵盖所有事实。

The key to wielding this powerful model is understanding when it works for you and when it works against you. A theory that is too simple will fail to capture reality, and one that is too complex will collapse under its own weight.

运用这一强大模型的关键在于理解它何时对你有利,何时对你不利。过于简单的理论无法捕捉现实,而过于复杂的理论则会因自身过于复杂而崩溃。

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Hanlon’s Razor

汉隆剃刀

Don’t assume the worst.

不要往最坏的方面想。

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I need to listen well so that I hear what is not said.

—Thuli Madonsela [1]

我需要认真倾听,才能听懂言外之意。——图莉·马东塞拉[1]
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Hard to trace in its origin, Hanlon’s razor states that we should not attribute to malice that which is more easily explained by stupidity. In a complex world, using this model helps us avoid paranoia and ideology. By not generally assuming that bad results are the fault of a bad actor, we look for options instead of missing opportunities. This model reminds us that people do make mistakes and demands that we ask if there is another reasonable explanation for the events that have occurred. The explanation most likely to be right is the one that contains the least amount of intent.

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汉隆剃刀原理起源难以追溯,它指出我们不应将那些更容易用愚蠢解释的事情归咎于恶意。在复杂的世界里,运用这一模型有助于我们避免妄想和意识形态的束缚。通过不总是假定糟糕的结果都是某个坏人的错,我们就能寻找其他可能性,而不是错失良机。这一模型提醒我们,人都会犯错,并要求我们探究事件发生后是否存在其他合理的解释。最有可能正确的解释往往是包含最少恶意成分的解释。

Assuming the worst intent is a habit that crops up all over our lives. Consider road rage, a growing problem in a world that is becoming short on patience and time. When someone cuts you off, to assume malice is to assume the other person has done a lot of risky work. In order for someone to deliberately get in your way, they have to notice you, gauge the speed of your car, consider where you are headed, and swerve in at exactly the right time to cause you to slam on the brakes, yet not cause an accident. That is some effort. The simpler, and thus more likely, explanation is that they didn’t see you. It was a mistake. There was no intent. So why would you assume the former? Why do our minds make these kinds of connections when logic says otherwise?

总是往最坏处想是生活中我们挥之不去的习惯。想想路怒症吧,在这个耐心和时间都日益匮乏的世界里,路怒症正成为一个日益严重的问题。当有人突然变道超车时,如果你认定对方心怀恶意,就等于认定对方做了件非常冒险的事。要故意挡你的路,他们必须注意到你,判断你的车速,考虑你的行驶方向,并且精准地在某个时刻突然变道,迫使你紧急刹车,同时又不能造成事故。这可不是件容易的事。更简单,也更合理的解释是,他们根本没看到你。这只是个误会。他们并没有恶意。那么,你为什么会先入为主地认为对方是恶意超车呢?为什么我们的大脑会在逻辑都否定这种可能性的情况下,仍然会做出这样的联想呢?

The famous Linda problem, demonstrated by the psychologists Daniel Kahneman and Amos Tversky in a 1982 paper, is an illuminating example of how our minds work and why we need Hanlon’s razor. [2] It went like this:

著名的琳达问题,由心理学家丹尼尔·卡尼曼和阿莫斯·特沃斯基在1982年的一篇论文中提出,生动地阐释了我们的思维运作方式以及为什么我们需要汉隆剃刀原理。[2] 问题如下:

Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.

Which is more probable?

  1. Linda is a bank teller.

  2. Linda is a bank teller and is active in the feminist movement.

琳达今年31岁,单身,性格直率,非常聪明。她大学主修哲学。学生时代,她就非常关注歧视和社会正义问题,也曾参加过反核示威活动。以下哪种可能性更大?琳达是一名银行柜员。琳达是一名银行柜员,并且积极参与女权运动。

The majority of respondents chose option 2. Why? The wording used to describe her suggests Linda is a feminist. But Linda could only be a bank teller, or a feminist and a bank teller. So naturally, the majority of students concluded she was both. They didn’t know anything about what she did, but because they were led to believe she had to be a feminist, they couldn’t reject that option, even though the math of statistics makes it more likely that a single condition is true instead of multiple conditions. In other words, every feminist bank teller is a bank teller, but not every bank teller is a feminist.

大多数受访者选择了选项2。为什么?对琳达的描述暗示她是一位女权主义者。但琳达要么是银行柜员,要么既是女权主义者又是银行柜员。因此,大多数学生自然而然地得出结论,认为她两者兼具。他们对琳达的职业一无所知,但由于被引导认为她一定是女权主义者,所以他们无法排除这个选项,即使统计学原理表明,单一条件成立的可能性远大于多个条件成立的可能性。换句话说,每个女权主义者银行柜员都是银行柜员,但并非每个银行柜员都是女权主义者。

Thus, Kahneman and Tversky showed that students would, with vivid enough wording, assume it more likely that a liberal-leaning woman was both a feminist and a bank teller rather than simply a bank teller. They called it the “conjunction fallacy.”

因此,卡尼曼和特沃斯基的研究表明,如果措辞足够生动,学生们会更倾向于认为一位倾向自由主义的女性既是女权主义者又是银行柜员,而不是仅仅是银行柜员。他们称之为“合取谬误”。

With this experiment, and a host of others, Kahneman and Tversky exposed a sort of tic in our mental machinery: We’re deeply affected by vivid, available evidence, to such a degree that we’re willing to make judgments that violate simple logic. We overconclude based on the available information; we have no trouble packaging in unrelated factors if they happen to occur in proximity to what we already believe.

通过这项实验以及其他一系列实验,卡尼曼和特沃斯基揭示了我们思维机制中的一种怪癖:我们极易受到生动、唾手可得的证据的影响,以至于我们愿意做出违背基本逻辑的判断。我们会根据现有信息得出过度结论;如果一些看似无关的因素恰好出现在我们已有信念的附近,我们也会毫不犹豫地将它们纳入考量。

The Linda problem was later criticized as the psychologists setting up their test subjects for failure—if the problem was stated in a different way, subjects did not always make the error. But this, of course, was Kahneman and Tversky’s point: If we present the evidence in a certain light, the brain malfunctions. It doesn’t weigh out the variables in a rational way.

后来有人批评“琳达问题”,认为心理学家故意让受试者犯错——如果换一种方式表述问题,受试者并非总是会犯错。但这恰恰是卡尼曼和特沃斯基的观点:如果我们以某种特定的方式呈现证据,大脑就会出现功能障碍,无法理性地权衡各种变量。

What does this have to do with Hanlon’s razor? When we see something happen that we don’t like and that seems wrong, we assume it’s intentional. But it’s more likely that it’s completely unintentional. Assuming someone is doing wrong and doing it purposefully is like assuming Linda is more likely to be a bank teller and a feminist. Most people doing wrong are not bad people trying to be malicious.

这和汉隆剃刀原理有什么关系呢?当我们看到一些我们不喜欢且看似错误的事情发生时,我们往往会认为这是故意的。但更有可能的是,这完全是无意的。假设某人做错事是故意的,就好比假设琳达更有可能既是银行柜员又是女权主义者一样。大多数做错事的人并非心怀恶意的坏人。

With such vividness of information, and the associated emotional response, comes a sort of malfunctioning in our minds when we’re trying to diagnose the causes of a bad situation. That’s why we need Hanlon’s razor as an important remedy. Failing to prioritize stupidity over malice causes things like paranoia. Always assuming malice puts you at the center of everyone else’s world. This is an incredibly self-centered and impractical approach to life. In reality, for every act of malice, there is almost certainly far more ignorance, stupidity, and laziness at work.

信息如此生动,随之而来的情绪反应也如此强烈,这导致我们在试图诊断糟糕情况的根源时,思维会出现某种程度的紊乱。这就是为什么我们需要汉隆剃刀原理作为重要的补救措施。如果不能将愚蠢置于恶意之上,就会引发诸如妄想症之类的问题。总是假定他人怀有恶意,会让你成为所有人世界的中心。这是一种极其以自我为中心且不切实际的生活方式。事实上,每一起恶意行为背后,几乎肯定存在着更多的无知、愚蠢和懒惰。

One is tempted to define man as a rational animal who always loses his temper when he is called upon to act in accordance with the dictates of reason.

—Oscar Wilde [3]

人们很容易将人定义为一种理性的动物,但当被要求按照理性行事时,他总是会失去理智。——奥斯卡·王尔德[3]

The End of an Empire

一个帝国的终结

In 408 AD, Honorius was the emperor of the Western Roman Empire. He assumed malicious intentions on the part of his best general, Stilicho, and had him executed. According to some historians, this execution may have been a key factor in the collapse of the empire. [4] , [5]

公元408年,霍诺留是西罗马帝国的皇帝。他怀疑自己最得力的将军斯提利科心怀不轨,便将其处死。一些历史学家认为,这次处决可能是帝国崩溃的关键因素之一。[4],[5]

Why? Stilicho was an exceptional military general who won many campaigns for Rome. He was also very loyal to the empire. He was not, however, perfect. Like all people, he made some decisions with negative outcomes. One of these was persuading the Roman Senate to accede to the demands of Alaric, leader of the Visigoths. Alaric had attacked the empire multiple times and was no favorite in Rome. The Senate didn’t want to give in to his threats and wanted to fight him.

为什么?斯提利科是一位杰出的军事将领,为罗马赢得了许多战役的胜利。他对帝国也十分忠诚。然而,他并非完美无缺。和所有人一样,他也做出了一些后果严重的决定。其中之一就是说服罗马元老院接受西哥特人首领阿拉里克的要求。阿拉里克曾多次入侵帝国,在罗马并不受待见。元老院不愿屈服于他的威胁,决心与他决一死战。

Stilicho counseled against this. Perhaps he had a relationship with Alaric and thought he could convince him to join forces and push back against the other invaders Rome was dealing with. Regardless of his reasoning, this action of Stilicho’s compromised his reputation.

斯提利科劝阻了这一做法。或许他与阿拉里克关系密切,认为可以说服他与罗马联手对抗其他入侵者。无论他的理由是什么,斯提利科的这一举动都损害了他的声誉。

Honorius was thus persuaded of the undesirability of having Stilicho around. Instead of defending him, or giving him the benefit of the doubt on the issue, Honorius assumed malicious intent behind Stilicho’s actions—that he wanted the throne for himself and so was making decisions to shore up his power. Honorius ordered the general’s arrest and likely supported his execution.

因此,霍诺留确信斯提利科的存在并非明智之举。他非但没有为斯提利科辩护,也没有对他抱有任何善意,反而认定斯提利科的行为别有用心——他觊觎王位,因此才做出种种巩固自身权力的决定。霍诺留下令逮捕了这位将军,并且很可能支持处决了他。

Without Stilicho to influence the relationship with the Visigoths, the empire became a military disaster. Alaric sacked Rome two years later, the first barbarian to capture the city in nearly eight centuries. Rome was thus compromised, a huge contributing factor to the collapse of the Western Roman Empire.

失去了斯提利科的斡旋,帝国与西哥特人的关系陷入混乱,军事上彻底崩溃。两年后,阿拉里克攻陷罗马,成为近八个世纪以来第一个攻占这座城市的蛮族。罗马因此遭受重创,这成为西罗马帝国灭亡的重要因素之一。

Hanlon’s razor, when practiced diligently as a counter to confirmation bias, empowers us, giving us far more realistic and effective options for remedying bad situations. When we assume someone is out to get us, our very natural instinct is to take action to defend ourselves. It’s harder to take advantage of, or even see, opportunities while in this defensive mode, because our priority is saving ourselves—which tends to reduce our vision to dealing with the perceived threat instead of examining the bigger picture.

汉隆剃刀原理若能被我们认真运用,作为对抗确认偏误的有效方法,便能赋予我们力量,让我们拥有更现实、更有效的应对困境的方案。当我们认定有人要害我们时,我们的本能反应便是采取行动自卫。在这种防御模式下,我们很难把握甚至发现机遇,因为我们的首要任务是自保——这往往会使我们的视野局限于应对感知到的威胁,而忽略了更宏观的层面。

The Man Who Saved the World

拯救世界的人

On October 27, 1962, Vasili Arkhipov stayed calm, didn’t assume malice, and saved the world. Seriously.

1962年10月27日,瓦西里·阿尔希波夫保持冷静,没有妄加揣测,拯救了世界。千真万确。

This was the height of the Cuban missile crisis. Tensions were high between the United States and the Soviet Union. The world felt on the verge of nuclear war—a catastrophic outcome for all.

当时正值古巴导弹危机的高峰期。美国和苏联之间的紧张局势高度紧张。世界感觉自己处于核战争的边缘——这对所有人来说都将是一场灾难性的后果。

American destroyers and Soviet subs were in a standoff in the waters off Cuba. Although they were technically in international waters, the Americans had informed the Soviets that they would be dropping blank depth charges to force the Soviet submarines to surface. The problem was, Soviet HQ had failed to pass this information along, so the subs in the area were ignorant of the planned American action. [6]

美国驱逐舰和苏联潜艇在古巴附近海域对峙。虽然严格来说,他们当时身处国际水域,但美国人已经告知苏联,他们将投掷空包深水炸弹,迫使苏联潜艇浮出水面。问题是,苏联总部未能将这一信息传达给美方,因此该区域的潜艇对美国的行动计划一无所知。[6]

Arkhipov was an officer aboard Soviet sub B-59—a sub that, unbeknownst to the Americans, was carrying a nuclear weapon. When the depth charges began to detonate above them, the Soviets onboard B-59 assumed the worst. Convinced that war had broken out, the captain of the sub wanted to arm and deploy the nuclear-tipped torpedo.

阿尔希波夫是苏联B-59号潜艇上的一名军官——这艘潜艇当时载有核武器,而美国人对此毫不知情。当深水炸弹开始在他们头顶爆炸时,B-59号上的苏联人预感情况非常糟糕。他们确信战争已经爆发,潜艇艇长想要启动并投放那枚装有核弹头的鱼雷。

This would have been an unprecedented disaster. It would have significantly changed the world as we know it, with both the geopolitical and nuclear fallout affecting us for decades. Luckily for us, the launch of the torpedo required all three senior officers onboard to agree, and Arkhipov didn’t. Instead of assuming malice, he stayed calm and insisted on surfacing to contact Moscow.

这本该是一场前所未有的灾难。它将彻底改变我们所知的世界,其地缘政治和核后果将影响我们数十年。幸运的是,鱼雷发射需要船上三名高级军官一致同意,而阿尔希波夫并没有同意。他没有妄加揣测,而是保持冷静,坚持浮出水面与莫斯科联系。

Although the explosions around the submarine could have been malicious, Arkhipov realized that to assume so would put the lives of billions in peril. Far better to suppose mistakes and ignorance and on that basis make the decision not to launch. In doing so, Arkhipov saved the entire world.

尽管潜艇周围的爆炸可能是人为恶意造成的,但阿尔希波夫意识到,如果这样假设,将会危及数十亿人的生命。更好的做法是假设是人为失误或无知,并在此基础上决定不发射潜艇。阿尔希波夫的这一决定拯救了全世界。

The sub surfaced and returned to Moscow. Arkhipov wasn’t hailed as a hero until the record was declassified, forty years later, and documents revealed just how close the world had come to nuclear war.

潜艇浮出水面,返回莫斯科。直到四十年后,相关记录解密,文件揭示了世界当时距离核战争有多么近,阿尔希波夫才被誉为英雄。

As useful as Hanlon’s razor can be, however, it is important not to overthink this model. Hanlon’s razor is meant to help us perceive stupidity, or error, and their inadvertent consequences. It says that of all possible motives behind an action, the ones that require the least amount of energy to execute (such as ignorance or laziness) are more likely to be at work than ones that require active malice.

尽管汉隆剃刀原理很有用,但重要的是不要过度解读这个模型。汉隆剃刀原理旨在帮助我们识别愚蠢或错误及其无意的后果。它指出,在所有可能的行动动机中,那些执行起来最省力的动机(例如无知或懒惰)比那些需要恶意才能实施的动机更有可能起作用。

Conclusion

结论

Hanlon’s razor is a mental safeguard against the temptation to label behavior as malicious when incompetence is the most common response. It’s a reminder that people are not out to get you and it’s best to assume good faith and resist the urge to assign sinister motives without overwhelming evidence.

汉隆剃刀原理是一种心理防御机制,它能帮助我们避免将他人的行为贴上恶意标签,因为最常见的解释往往是能力不足。它提醒我们,人们并非有意针对我们,最好是假设对方是出于善意,并在没有确凿证据的情况下,克制住妄加揣测他人动机的冲动。

This isn’t to say that genuine malice doesn’t exist. Of course it does. But in most interactions, stupidity is a far more common explanation than malevolence. People make mistakes. They forget things. They speak without thinking. They prioritize short-term wins over long-term wins. They act on incomplete information. They fall prey to bias and prejudice. From the outside, these actions might appear like deliberate attacks, but the reality is far more mundane.

这并非否认真正的恶意存在。当然,恶意是存在的。但在大多数交往中,愚蠢远比恶意更为常见。人都会犯错。他们会忘记事情。他们会不假思索地说话。他们会优先考虑短期利益而非长期利益。他们会基于不完整的信息采取行动。他们会受到偏见和成见的影响。从表面上看,这些行为或许像是蓄意攻击,但实际上却远比这平凡得多。

The real power of Hanlon’s razor lies in the way it shifts our perspective. When we assume stupidity rather than malice, we respond differently. Instead of getting defensive or lashing out, we approach the situation with empathy and clarity.

汉隆剃刀的真正威力在于它转变了我们的视角。当我们假设对方是出于愚蠢而非恶意时,我们的反应就会截然不同。我们不会采取防御姿态或进行反击,而是会以同理心和清晰的思路来处理问题。

For most of the daily frustrations and confusions, Hanlon’s razor is a powerful reminder to approach problems with a spirit of generosity. It’s a way to reduce the drama and stress in our lives, and to find practical solutions instead of descending into blame and recrimination.

对于日常生活中大多数的挫折和困惑,汉隆剃刀原理都能有力地提醒我们,要以宽容的精神来处理问题。它能帮助我们减少生活中的戏剧性和压力,找到切实可行的解决方案,而不是陷入相互指责和推诿。

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Afterthoughts and Acknowledgments

后记与致谢

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Afterthoughts

后记

Many of you are no doubt wondering why I choose to partner with Portfolio and rerelease these books. The answer isn’t complicated. First, I wanted to spend less time on the nuts and bolts of running a publishing business (which includes creating, designing, printing, managing inventory, managing relationships, and increasingly complicated tax reporting requirements) and more time on the podcast, newsletter, and helping people become the best version of themselves. Second, I like and trust the team at Portfolio, led by Niki Papadopoulos.

想必很多人都想知道我为什么选择与 Portfolio 合作并重新发行这些书籍。答案其实很简单。首先,我希望减少在出版业务的繁琐事务上花费的时间(包括创作、设计、印刷、库存管理、客户关系维护以及日益复杂的税务申报要求),从而将更多精力投入到播客、电子报刊以及帮助人们成为更好的自己。其次,我欣赏并信任 Portfolio 团队,尤其是 Niki Papadopoulos 领导的团队。

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Acknowledgments

致谢

I’m forever indebted to Charlie Munger, Peter D. Kaufman, Warren Buffett, and Peter Bevelin, who, to varying degrees, started me down the path of multidisciplinary thinking. I owe them a huge debt of gratitude.

我永远感激查理·芒格、彼得·考夫曼、沃伦·巴菲特和彼得·贝弗林,他们不同程度地引领我走上了跨学科思考的道路。我对他们感激不尽。

Thank you to my coauthor, Rhiannon Beaubien, for making this series possible. It’s impossible to overstate her contributions to this volume and the entire series. Without her, you would not be holding this book in your hands.

感谢我的合著者瑞安农·博比恩,是她让这套丛书得以出版。她对本书乃至整个系列的贡献怎么强调都不为过。没有她,你们就不会拥有这本书。

This series would be lost without our talented illustrator, Marcia Mihotich. Thank you for seeing these words and ideas and bringing them to life in simple and exceptional ways.

如果没有我们才华横溢的插画师玛西娅·米霍蒂奇,这个系列就不会如此精彩。感谢你理解这些文字和想法,并以简洁而卓越的方式将它们生动地呈现出来。

While this is a revised volume 1, I wanted to give a special mention to Garvin Hirt and Morgwn Rimel for shaping the creativity of the original version. Working with you both has encouraged me to make things beautiful and timeless. And thank you to Néna Rawdah and our OG editor Kristen Hall-Geisler for her willingness to dive in and ensure the material flows and comes together in the end.

虽然这是第一卷的修订版,但我还是要特别感谢 Garvin Hirt 和 Morgwn Rimel,感谢他们对原版创意的塑造。与你们两位的合作激励我创作出既美观又经久不衰的作品。同时,我也要感谢 Néna Rawdah 和我们的元老级编辑 Kristen Hall-Geisler,感谢她们的积极参与,确保最终的成书流畅自然。

The original version of this series would not have been possible without our partnership with Automattic and their incredible CEO, Matt Mullenweg. Thank you to Niki Papadopoulos and the entire team at Portfolio for rereleasing this series and supporting my efforts to make it as beautiful and as timeless as we can.

如果没有与 Automattic 及其杰出的首席执行官 Matt Mullenweg 的合作,本系列的最初版本是不可能实现的。感谢 Niki Papadopoulos 和 Portfolio 的全体团队成员重新发行本系列,并支持我努力使其尽可能精美且经久不衰。

Thank you to Simon Hørup Eskildsen, Zachary Smith, Paul Ciampa, Devon Anderson, Alex Duncan, Vicky Cosenzo, Laurence Endersen, David Epstein, Ozan Gurcan, Will Bowers, Ran Klein, Sanjay Bakshi, Jeff Annello, Tara Small, Tina Cantrill, Nathan Taggart, Tim Bragassa, Yves Colomb, Rick Jones, Maria Petrova, and Dr. Gregory P. Moore for taking the time to review books in this series. Your comments and contributions have helped make everything better.

感谢 Simon Hørup Eskildsen、Zachary Smith、Paul Ciampa、Devon Anderson、Alex Duncan、Vicky Cosenzo、Laurence Endersen、David Epstein、Ozan Gurcan、Will Bowers、Ran Klein、Sanjay Bakshi、Jeff Annello、Tara Small、Tina Cantrill、Nathan Taggart、Tim Bragassa、Yves Colomb、Rick Jones、Maria Petrova 以及 Gregory P. Moore 博士抽出宝贵时间审阅本系列书籍。你们的评论和贡献使一切都变得更好。

Thank you to my sons, Will and Mack, for reminding me to continue to learn and grow along with you. This series was largely written for you and future generations.

感谢我的儿子威尔和马克,是他们提醒我要和你们一起不断学习和成长。这套丛书主要是为你们以及未来的孩子们而写的。

Thank you to the entire Farnam Street team for your hard work and dedication over the years to bring this series to life.

感谢 Farnam Street 团队多年来的辛勤工作和奉献精神,使这部剧集得以问世。

And finally, thanks to you, the reader. I continue to be amazed by how many of you want to take this mental-models journey with me. I hope this book is one you can reference time and again as you seek to better understand the world.

最后,感谢各位读者。你们当中有这么多人愿意与我一同踏上这段探索心智模型的旅程,这让我感到无比惊喜。我希望这本书能成为你们反复参考的宝贵资料,帮助你们更好地理解这个世界。

Shane

肖恩

#

Notes

笔记

Introduction: Acquiring Wisdom

引言:获得智慧

  1. Shane Parrish, “Peter Bevelin on Seeking Wisdom, Mental Models, Learning, and a Lot More,” Farnam Street (blog), accessed January 30, 2024, fs.blog/2016/10/peter-bevelin-seeking-wisdom-mental-models/ .

    Shane Parrish,“Peter Bevelin 论寻求智慧、心智模型、学习等等”,Farnam Street(博客),访问日期:2024 年 1 月 30 日,网址:fs.blog/2016/10/peter-bevelin-seeking-wisdom-mental-models/。

  2. Robert Graves, The Greek Myths , rev. ed. (London: The Folio Society, 1996).

    Robert Graves,《希腊神话》,修订版(伦敦:Folio Society,1996 年)。

  3. Thomas Bulfinch, The Golden Age of Myth and Legend (Stansted, UK: Wordsworth Editions, 1993).

    Thomas Bulfinch,《神话与传说的黄金时代》(英国斯坦斯特德:Wordsworth Editions,1993 年)。

  4. David Foster Wallace, “This Is Water: Some Thoughts, Delivered on a Significant Occasion, about Living a Compassionate Life,” Farnam Street (blog), accessed March 8, 2024, fs.blog/david-foster-wallace-this-is-water .

    David Foster Wallace,“这就是水:在重要场合发表的一些关于过上慈悲生活的想法”,Farnam Street(博客),访问日期:2024 年 3 月 8 日,网址:fs.blog/david-foster-wallace-this-is-water。

  5. Charles Darwin, The Autobiography of Charles Darwin: 1809–1882 , reissue, Nora Barlow, ed. (New York: W. W. Norton & Company, 1996).

    查尔斯·达尔文,《查尔斯·达尔文自传:1809-1882》,再版,诺拉·巴洛编辑(纽约:W. W. Norton & Company,1996 年)。

  6. Andy Benoit, “The Case for the…Broncos,” Sports Illustrated , January 13, 2014, vault.si.com/vault/2014/01/13/the-case-for-the-broncos .

    Andy Benoit,“支持…野马队的理由”,《体育画报》,2014 年 1 月 13 日,vault.si.com/vault/2014/01/13/the-case-for-the-broncos。

  7. The best way to reflect can be found here: Shane Parrish, “Writing to Think,” Farnam Street (blog), accessed February 1, 2024, fs.blog/writing-to-think/ .

    反思的最佳方法可以在这里找到:Shane Parrish,“写作思考”,Farnam Street(博客),访问日期:2024 年 2 月 1 日,网址:fs.blog/writing-to-think/。

  8. Peter D. Kaufman, as found in Joe Koster, “East Coast Asset Management’s Q3 2014 Investment Letter: Grove of Titans,” Value Investing World (blog), November 10, 2014, https://www.valueinvestingworld.com/2014/11/east-coast-asset-managements-q3-2014.html .

    Peter D. Kaufman,摘自 Joe Koster,“东海岸资产管理公司 2014 年第三季度投资简报:巨头林”,价值投资世界(博客),2014 年 11 月 10 日,https://www.valueinvestingworld.com/2014/11/east-coast-asset-managements-q3-2014.html。

  9. Brent Schlender, “The Bill and Warren Show,” Fortune , July 20, 1998, https://money.cnn.com/magazines/fortune/fortune_archive/1998/07/20/245683/ .

    Brent Schlender,“比尔和沃伦秀”,《财富》,1998 年 7 月 20 日,https://money.cnn.com/magazines/fortune/fortune_archive/1998/07/20/245683/。

  10. Charles Munger, “A Lesson on Elementary, Worldly Wisdom as It Relates to Investment Management and Business,” (lecture, USC Marshall School of Business, Los Angeles, CA, 1994), as found in Shane Parrish, “A Lesson on Elementary Worldly Wisdom as It Relates to Investment Management & Business,” Farnam Street (blog), accessed February 2, 2024, fs.blog/great-talks/a-lesson-on-worldly-wisdom/ .

    查尔斯·芒格,“关于与投资管理和商业相关的基本世俗智慧的一课”(1994 年在南加州大学马歇尔商学院的演讲),出自 Shane Parrish,“关于与投资管理和商业相关的基本世俗智慧的一课”,Farnam Street(博客),访问日期:2024 年 2 月 2 日,网址:fs.blog/great-talks/a-lesson-on-worldly-wisdom/。

  11. Alain de Botton and Diyala Muir, “How to Make a Decision,” The School of Life, November 2, 2017, video, 6:22, youtu.be/okdsAZUTJ94 .

    阿兰·德波顿和迪亚拉·缪尔,“如何做出决定”,人生学校,2017 年 11 月 2 日,视频,6:22,youtu.be/okdsAZUTJ94。

  12. Munger, “A Lesson on Elementary, Worldly Wisdom.”

    芒格,《论基本的世俗智慧》。

  13. Charlie Munger, Poor Charlie’s Almanack (China: Tsai Fong Books, 2014).

    查理·芒格,《穷查理宝典》(中国:蔡丰出版社,2014年)。

  14. Herbert A. Simon, Models of My Life (Cambridge, MA: MIT Press, 1996).

    Herbert A. Simon,《我的人生模型》(马萨诸塞州剑桥:麻省理工学院出版社,1996 年)。

The Map Is Not the Territory

地图并非疆域本身

  1. George Box and Norman Draper, Empirical Model Building and Response Surfaces (Hoboken, NJ: Wiley, 1987).

    George Box 和 Norman Draper,《经验模型构建和响应曲面》(新泽西州霍博肯:Wiley,1987 年)。

  2. See at 1:33:56 in Lex Fridman, “Jeff Bezos: Amazon and Blue Origin,” December 14, 2023, Lex Fridman Podcast , episode 405, video, 2:11:31, youtube.com/watch?v=DcWqzZ3I2cY .

    参见 Lex Fridman 的《Jeff Bezos: Amazon and Blue Origin》,2023 年 12 月 14 日,Lex Fridman Podcast,第 405 集,视频,2:11:31,youtube.com/watch?v=DcWqzZ3I2cY,1:33:56。

  3. Alfred Korzybski, Science and Sanity: An Introduction to Non-Aristotelian Systems and General Semantics (New York: Institute of General Semantics, 1933).

    Alfred Korzybski,《科学与理智:非亚里士多德体系和一般语义学导论》(纽约:一般语义学研究所,1933 年)。

  4. Aristotle, Politics , Benjamin Jowett, trans. (South Kitchener, Ontario: Batoche Books, 1999).

    亚里士多德,《政治学》,本杰明·乔维特译(安大略省南基奇纳:巴托什出版社,1999 年)。

  5. Garrett Hardin, “The Tragedy of the Commons,” Science 162, no. 3859 (1968): 1243–48.

    Garrett Hardin,“公地悲剧”,《科学》162,第3859期(1968年):1243-48。

  6. Elinor Ostrom, Governing the Commons: The Evolution of Institutions for Collective Action (Cambridge, UK: Cambridge University Press, 1990).

    Elinor Ostrom,《公共领域的治理:集体行动制度的演变》(英国剑桥:剑桥大学出版社,1990 年)。

  7. Issam Nassar, “Early Local Photography in Palestine: The Legacy of Karimeh Abbud,” Jerusalem Quarterly , no. 46 (Summer 2011).

    Issam Nassar,“巴勒斯坦早期地方摄影:Karimeh Abbud 的遗产”,《耶路撒冷季刊》,第 46 期(2011 年夏季)。

  8. Ahmed Mrowat, “Karimeh Abbud: Early Woman Photographer (1896–1955),” Jerusalem Quarterly , no. 31 (Summer 2007).

    Ahmed Mrowat,“Karimeh Abbud:早期女摄影师(1896–1955)”,《耶路撒冷季刊》,第 31 期(2007 年夏季)。

  9. Norman J. W. Thrower, Maps and Civilization: Cartography in Culture and Society (Chicago: University of Chicago Press, 1999).

    Norman J. W. Thrower,《地图与文明:文化与社会中的制图学》(芝加哥:芝加哥大学出版社,1999 年)。

  10. Margaret MacMillan, The Uses and Abuses of History (Toronto: Penguin, 2008).

    玛格丽特·麦克米伦,《历史的用途和滥用》(多伦多:企鹅出版社,2008 年)。

  11. An excellent analysis of the division of the Middle East after World War I can be found in Margaret MacMillan, Paris 1919: Six Months That Changed the World (New York: Random House, 2001).

    玛格丽特·麦克米伦 (Margaret MacMillan) 的《巴黎 1919:改变世界的六个月》(纽约:兰登书屋,2001 年) 对第一次世界大战后中东的分裂进行了精彩的分析。

  12. Jane Jacobs, The Death and Life of Great American Cities , rev. ed. (New York: Vintage Books, 1992), 438.

    Jane Jacobs,《美国大城市的死与生》,修订版(纽约:Vintage Books,1992 年),第 438 页。

  13. David J. Hand, “Wonderful Examples, But Let’s Not Close Our Eyes,” Statistical Science 29, no. 1 (2014), 98–100.

    David J. Hand,“精彩的例子,但我们不能闭上眼睛”,统计科学 29,第 1 期(2014 年),98-100 页。

Circle of Competence

能力圈

  1. Thomas J. Watson and Peter Petre, Father, Son, and Co.: My Life at IBM and Beyond (New York: Random House, 2000).

    Thomas J. Watson 和 Peter Petre,《父子情深:我在 IBM 及以后的生活》(纽约:兰登书屋,2000 年)。

  2. Sun Tzu, The Art of War , Lionel Giles, trans. (Los Angeles, Enhanced Media, 2017).

    孙子兵法,莱昂内尔·吉尔斯译(洛杉矶,Enhanced Media,2017)。

  3. Robert Peirce, “Biography,” SherpaTenzingNorgay.com, accessed February 5, 2024, sherpatenzingnorgay.com/bio.html ; Grayson Schaffer, “The Disposable Man: A Western History of Sherpas on Everest,” Outside , July 10, 2013, outsideonline.com/1928326/disposable-man-western-history-sherpas-everest .

    Robert Peirce,“传记”,SherpaTenzingNorgay.com,访问日期:2024 年 2 月 5 日,sherpatenzingnorgay.com/bio.html;Grayson Schaffer,“一次性人:珠穆朗玛峰上的夏尔巴人的西方历史”,《户外》,2013 年 7 月 10 日,outsideonline.com/1928326/disposable-man-western-history-sherpas-everest。

  4. David Roberts, “Everest 1953: First Footsteps—Sir Edmund Hillary and Tenzing Norgay,” National Geographic , March 3, 2013, nationalgeographic.com/adventure/features/everest/sir-edmund-hillary-tenzing-norgay-1953/ .

    David Roberts,“珠穆朗玛峰 1953:第一步——埃德蒙·希拉里爵士和丹增·诺尔盖”,《国家地理》,2013 年 3 月 3 日,nationalgeographic.com/adventure/features/everest/sir-edmund-hillary-tenzing-norgay-1953/。

  5. Schaffer, “The Disposable Man.”

    沙弗,《一次性人》。

  6. Charlie Munger, Poor Charlie’s Almanack . (China: Tsai Fong Books, 2014)

    查理·芒格,《穷查理宝典》(中国:蔡丰出版社,2014年)。

  7. Alexander Pope, “An Essay on Criticism.” Poetry Foundation, accessed February 11, 2024, poetryfoundation.org/articles/69379/an-essay-on-criticism .

    Alexander Pope,“论批评”。诗歌基金会,访问日期:2024 年 2 月 11 日,poetryfoundation.org/articles/69379/an-essay-on-criticism。

  8. Charles Munger, untitled speech (Daily Journal Corporation annual meeting, Cathedral of Our Lady of the Angels, Los Angeles, CA, February 12, 2020) as transcribed at Oliver Sung, “Charlie Munger: 2020 Daily Journal Annual Meeting Transcript,” Junto, accessed February 11, 2024, junto.investments/charlie-munger-daily-journal-2020-transcript.

    查理·芒格,无标题演讲(《每日新闻》公司年会,洛杉矶天使之后大教堂,加利福尼亚州,2020 年 2 月 12 日),摘自 Oliver Sung 的文章“查理·芒格:2020 年《每日新闻》年会记录”,Junto,访问日期:2024 年 2 月 11 日,网址:junto.investments/charlie-munger-daily-journal-2020-transcript。

  9. Atul Gawande, “Personal Best,” New Yorker , October 3, 2011, newyorker.com/magazine/2011/10/03/personal-best .

    Atul Gawande,“个人最佳”,《纽约客》,2011 年 10 月 3 日,newyorker.com/magazine/2011/10/03/personal-best。

  10. Part of understanding circles of competence is knowing when you’re not the best person to make the decision and allowing someone else with a comparative advantage in this area to make the decision instead.

    理解能力圈的一部分在于知道什么时候你不是做决定的最佳人选,并允许在该领域具有比较优势的人来做决定。

  11. Elizabeth Tudor, “Wordes Spoken by the Queene to the Lordes” (speech to members of the House of Lords, Hatfield, November 20, 1558), as found in “Elizabeth’s First Speech,” National Archives, accessed February 11, 2024, https://www.nationalarchives.gov.uk/education/resources/elizabeth-monarchy/elizabeths-first-speech/ .

    伊丽莎白·都铎,《女王对上议院议员的讲话》(1558 年 11 月 20 日在哈特菲尔德向上议院议员发表的讲话),出自《伊丽莎白的第一次演讲》,国家档案馆,2024 年 2 月 11 日访问,https://www.nationalarchives.gov.uk/education/resources/elizabeth-monarchy/elizabeths-first-speech/。

  12. Peter Brimacombe, All the Queen’s Men: The World of Elizabeth I (New York: St. Martin’s Press, 2000).

    Peter Brimacombe,《女王的所有臣民:伊丽莎白一世的世界》(纽约:圣马丁出版社,2000 年)。

  13. Charles Darwin, The Descent of Man, and Selection in Relation to Sex (New York: D. Appleton and Company, 1882).

    查尔斯·达尔文,《人类的由来及性选择》(纽约:D. Appleton and Company,1882 年)。

  14. Warren Buffett, “Lecture to Faculty” (lecture, Notre Dame University, South Bend, IN, 1991), as found on Whitney Tilson’s Value Investing website, accessed February 11, 2024, tilsonfunds.com/BuffettNotreDame.pdf .

    沃伦·巴菲特,“对教职员工的演讲”(1991 年在印第安纳州南本德圣母大学的演讲),摘自 Whitney Tilson 的价值投资网站,访问日期为 2024 年 2 月 11 日,tilsonfunds.com/BuffettNotreDame.pdf。

  15. Popper’s theories on falsifiability as given here are taken from his books The Logic of Scientific Discovery , The Poverty of Historicism , and All Life Is Problem Solving . The quoted material is taken from Karl Popper, The Logic of Scientific Discovery (London: Hutchinson & Co., 1959).

    本文中波普尔关于可证伪性的理论摘自他的著作《科学发现的逻辑》、《历史主义的贫困》和《一切生命都是问题解决》。引文出自卡尔·波普尔的《科学发现的逻辑》(伦敦:哈钦森出版社,1959年)。

  16. Popper, The Logic of Scientific Discovery .

    波普尔,《科学发现的逻辑》。

  17. Bertrand Russell, The Problems of Philosophy (New York: Henry Holt and Company, 1912).

    伯特兰·罗素,《哲学问题》(纽约:亨利·霍尔特公司,1912 年)。

First Principles Thinking

第一性原理思维

  1. Ralph Leighton, Surely You’re Joking, Mr. Feynman: Adventures of a Curious Character (New York: Random House, 2014).

    拉尔夫·莱顿,《费曼先生,您肯定是在开玩笑吧:一个好奇人物的冒险》(纽约:兰登书屋,2014 年)。

  2. Thanks go to James Clear for the conversation that inspired my thinking here. For more about first principles thinking, see James Clear, “First Principles: Elon Musk on the Power of Thinking for Yourself,” JamesClear.com, accessed February 11, 2024, jamesclear.com/first-principles .

    感谢 James Clear 的对话启发了我在此的思考。有关第一性原理思考的更多信息,请参阅 James Clear 的文章“第一性原理:埃隆·马斯克论独立思考的力量”,JamesClear.com,访问日期:2024 年 2 月 11 日,网址:jamesclear.com/first-principles。

  3. Carl Sagan, “Why We Need to Understand Science,” Skeptical Inquirer 14, no. 3 (Spring 1990): 263–269.

    卡尔·萨根,“为什么我们需要了解科学”,《怀疑论者》14,第3期(1990年春季):263-269。

  4. Kevin Ashton, How to Fly a Horse: The Secret History of Creation, Invention, and Discovery (New York: Anchor Books, 2015).

    凯文·阿什顿,《如何让马飞翔:创造、发明和发现的秘密历史》(纽约:Anchor Books,2015 年)。

  5. Pamela Weintraub, “The Doctor Who Drank Infectious Broth, Gave Himself an Ulcer, and Solved a Medical Mystery,” Discover , March 2010, discovermagazine.com/health/the-doctor-who-drank-infectious-broth-gave-himself-an-ulcer-and-solved-a-medical-mystery .

    Pamela Weintraub,“喝了传染性肉汤,得了溃疡,却解开了一个医学谜团的医生”,《发现》杂志,2010 年 3 月,discovermagazine.com/health/the-doctor-who-drank-infectious-broth-gave-himself-an-ulcer-and-solved-a-medical-mystery。

  6. Ashton, How to Fly a Horse .

    阿什顿,《如何让马飞翔》。

  7. Temple Grandin, “Livestock Handling Systems, Cattle Corrals, Stockyards, and Races,” Grandin.com, accessed February 11, 2024, grandin.com/design/design.html .

    Temple Grandin,“牲畜处理系统、牛栏、牲畜交易市场和通道”,Grandin.com,访问日期:2024 年 2 月 11 日,grandin.com/design/design.html。

  8. Temple Grandin, “A Response to Hibbard and Locatelli,” Stockmanship Journal 3, no. 1 (January 2014): 24–25.

    Temple Grandin,“对 Hibbard 和 Locatelli 的回应”,畜牧业杂志 3,第 1 期(2014 年 1 月):24-25。

  9. Harrington Emerson, speech published in “The Convention: Fifteenth Annual Convention of the National Association of Clothiers, held June 5 and 6, 1911,” Clothier and Furnisher 78, no. 6 (July 1911).

    哈灵顿·爱默生在《大会:全国服装商协会第十五届年会,1911 年 6 月 5 日至 6 日举行》一文中发表了演讲,该演讲刊登于《服装商和家具商》杂志第 78 卷第 6 期(1911 年 7 月)。

Thought Experiment

思想实验

  1. John C. Maxwell, Thinking for a Change: 11 Ways Highly Successful People Approach Life and Work (New York: Warner Books, 2003), 107.

    John C. Maxwell,《改变思维:成功人士对待生活和工作的 11 种方式》(纽约:华纳图书公司,2003 年),第 107 页。

  2. James Robert Brown and Yiftach Fehige, “Thought Experiments,” The Stanford Encyclopedia of Philosophy (Summer 2017 edition), Edward N. Zalta (ed.), https://plato.stanford.edu/archives/sum2017/entries/thought-experiment/ .

    James Robert Brown 和 Yiftach Fehige,“思想实验”,《斯坦福哲学百科全书》(2017 年夏季版),Edward N. Zalta(编),https://plato.stanford.edu/archives/sum2017/entries/thought-experiment/。

  3. Warren Buffet, untitled lecture (Warrington College of Business, University of Florida, Gainesville, October 15, 1998), as found on Whitney Tilson’s Value Investing website, accessed February 11, 2024, tilsonfunds.com/BuffettUofFloridaspeech.pdf .

    沃伦·巴菲特,无题演讲(佛罗里达大学沃灵顿商学院,盖恩斯维尔,1998 年 10 月 15 日),摘自 Whitney Tilson 的价值投资网站,访问日期为 2024 年 2 月 11 日,tilsonfunds.com/BuffettUofFloridaspeech.pdf。

  4. Walter Isaacson, Einstein: His Life and Universe (New York: Simon and Schuster, 2007).

    沃尔特·艾萨克森,《爱因斯坦:他的一生和宇宙》(纽约:西蒙与舒斯特出版社,2007 年)。

  5. Philippa Foot, “The Problem of Abortion and the Doctrine of the Double Effect,” Oxford Review , no. 5 (1967); Judith Jarvis Thomson, “The Trolley Problem,” Yale Law Journal 94, no. 6 (May 1985).

    Philippa Foot,“堕胎问题与双重效应原则”,《牛津评论》,第 5 期(1967 年);Judith Jarvis Thomson,“电车难题”,《耶鲁法律杂志》94,第 6 期(1985 年 5 月)。

  6. John Rawls, A Theory of Justice , rev. ed. (Cambridge, MA: Harvard University Press, 2005).

    约翰·罗尔斯,《正义论》,修订版(马萨诸塞州剑桥:哈佛大学出版社,2005 年)。

Second-Order Thinking

二阶思维

  1. Evelyn Fox Keller, A Feeling for the Organism: The Life and Work of Barbara McClintock (New York: W. H. Freeman and Company, 1983).

    Evelyn Fox Keller,《对有机体的感觉:芭芭拉·麦克林托克的生活和工作》(纽约:W. H. Freeman and Company,1983 年)。

  2. Margaret Atwood, Surfacing (Toronto: McClelland and Stewart, 1972).

    玛格丽特·阿特伍德,《表面》(多伦多:麦克莱兰和斯图尔特出版社,1972 年)。

  3. Garrett Hardin, Living Within Limits (New York: Oxford University Press, 1993).

    Garrett Hardin,《生活在限制之内》(纽约:牛津大学出版社,1993 年)。

  4. John Muir, My First Summer in the Sierra (Boston: Houghton Mifflin, 1911).

    约翰·缪尔,《我在内华达山脉的第一个夏天》(波士顿:霍顿·米夫林出版社,1911 年)。

  5. Warren Buffett, “Letter to Shareholders, 1985,” dated March 4, 1986, BerkshireHathaway.com, accessed February 13, 2024, berkshirehathaway.com/letters/1985.html .

    沃伦·巴菲特,《致股东的信,1985》,1986 年 3 月 4 日,BerkshireHathaway.com,2024 年 2 月 13 日访问,berkshirehathaway.com/letters/1985.html。

  6. Stacy Schiff, Cleopatra: A Life (New York: Back Bay Books, 2010).

    Stacy Schiff,《克利奥帕特拉:一生》(纽约:Back Bay Books,2010 年)。

  7. Ibid.

    同上。

  8. Ibid.

    同上。

  9. Elinor Ostrom and James Walker, eds., Trust and Reciprocity: Interdisciplinary Lessons from Experimental Research (New York: Russell Sage Foundation, 2003).

    Elinor Ostrom 和 James Walker 编辑,《信任与互惠:实验研究的跨学科经验》(纽约:罗素·塞奇基金会,2003 年)。

  10. Mary Wollstonecraft, A Vindication of the Rights of Woman , KNARF, Department of English, University of Pennsylvania, accessed March 11, 2024, Wollstonecraft, Vindication of the Rights of Woman (upenn.edu).

    Mary Wollstonecraft,《女权辩护》,KNARF,宾夕法尼亚大学英语系,2024 年 3 月 11 日访问,Wollstonecraft,《女权辩护》(upenn.edu)。

  11. Garrett Hardin, Filters Against Folly: How to Survive Despite Economists, Ecologists, and the Merely Eloquent (New York: Penguin, 1985).

    Garrett Hardin,《抵御愚昧:如何在经济学家、生态学家和雄辩家面前生存》(纽约:企鹅出版社,1985 年)。

Probabilistic Thinking

概率思维

  1. Benoit B. Mandelbrot, The Fractal Geometry of Nature (New York: W. H. Freeman and Company, 1977).

    Benoit B. Mandelbrot,《自然的分形几何》(纽约:W. H. Freeman and Company,1977 年)。

  2. Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable , 2nd ed. (New York: Random House, 2010).

    纳西姆·尼古拉斯·塔勒布,《黑天鹅:高度不可能事件的影响》,第2版(纽约:兰登书屋,2010年)。

  3. Peter L. Bernstein, Against the Gods: The Remarkable Story of Risk (New York: John Wiley and Sons, 1996). This book includes an excellent discussion, in chapter 13, on the idea of the scope of events in the past as relevant to figuring out the probability of events in the future, drawing on the work of Frank Knight and John Maynard Keynes.

    彼得·L·伯恩斯坦,《与神对抗:风险的非凡故事》(纽约:约翰·威利父子出版社,1996年)。本书第13章对过去事件的范围与推断未来事件概率之间的关系进行了精彩的讨论,并借鉴了弗兰克·奈特和约翰·梅纳德·凯恩斯的著作。

  4. Nassim Nicholas Taleb, Antifragile: Things That Gain from Disorder (New York: Random House, 2012).

    纳西姆·尼古拉斯·塔勒布,《反脆弱:从混乱中获益》(纽约:兰登书屋,2012 年)。

  5. Ibid.

    同上。

  6. Sarah Helm, A Life in Secrets: Vera Atkins and the Lost Agents of SOE (London: Abacus, 2006).

    Sarah Helm,《秘密人生:维拉·阿特金斯与特别行动执行处失踪特工》(伦敦:Abacus出版社,2006年)。

  7. Daniel Kahneman, Thinking, Fast and Slow (New York: Random House, 2011).

    丹尼尔·卡尼曼,《思考,快与慢》(纽约:兰登书屋,2011 年)。

Inversion

倒置

  1. F. Scott Fitzgerald, “The Crack-Up, Part I,” Esquire , February 1936.

    F·斯科特·菲茨杰拉德,《崩溃,第一部分》,《绅士》,1936 年 2 月。

  2. Charles Munger, interview by Becky Quick, Charlie Munger: A Life of Wit and Wisdom , CNBC, November 30, 2023, cnbc.com/amp/2023/11/30/full-transcript-from-cnbcs-charlie-munger-a-life-of-wit-and-wisdom-.html .

    查理·芒格,贝基·奎克采访,查理·芒格:充满智慧的一生,CNBC,2023 年 11 月 30 日,cnbc.com/amp/2023/11/30/full-transcript-from-cnbcs-charlie-munger-a-life-of-wit-and-wisdom-.html。

  3. Carl Jacobi’s famous maxim “Invert, always invert” (“man muss immer umkehren”) was not originally detailed in a specific publication by Jacobi himself but is often attributed to him as an expression of his problem-solving approach. The phrase has been popularized through various secondary sources discussing his mathematical philosophy and methodology.

    卡尔·雅可比的名言“反转,永远反转”(“man muss immer umkehren”)并非雅可比本人在其特定著作中详细阐述,但常被认为是雅可比解决问题的方法论的体现。这句格言通过各种探讨其数学哲学和方法论的二手资料而广为人知。

  4. Thomas Heath, A History of Greek Mathematics, vol. 1, From Thales to Euclid (Oxford, UK: Oxford University Press, 1921).

    Thomas Heath,《希腊数学史》第 1 卷,从泰勒斯到欧几里得(英国牛津:牛津大学出版社,1921 年)。

  5. Alan Axelrod, Profiles in Folly: History’s Worst Decisions and Why They Went Wrong (New York: Sterling, 2008).

    艾伦·阿克塞尔罗德,《愚蠢的剖析:历史上最糟糕的决定及其失败的原因》(纽约:斯特林出版社,2008 年)。

  6. Larry Tye, The Father of Spin: Edward L. Bernays and the Birth of Public Relations (New York: Henry Holt and Company, 1998).

    Larry Tye,《公关之父:爱德华·L·伯内斯与公共关系的诞生》(纽约:亨利·霍尔特公司,1998 年)。

  7. Axelrod, Profiles in Folly .

    阿克塞尔罗德,《愚行中的轮廓》。

  8. Ibid.

    同上。

  9. Tye, The Father of Spin .

    泰伊,旋转之父。

  10. John Bogle, Common Sense on Mutual Funds: New Imperatives for the Intelligent Investor (New York: John Wiley and Sons, 1999).

    John Bogle,《共同基金常识:精明投资者的新要求》(纽约:John Wiley and Sons,1999 年)。

  11. Charles Munger, speech (Harvard School, Cambridge, MA, June 13, 1986), as found in Alec Hogg, “Simply Great: Charlie Munger’s Speech to the Harvard School, June 1986—‘Invert, Always Invert,’ ” BizNews, accessed February 14, 2024, biznews.com/thought-leaders/1986/06/13/charlie-mungers-speech-to-the-harvard-school-june-1986 .

    查尔斯·芒格的演讲(1986 年 6 月 13 日,马萨诸塞州剑桥市哈佛商学院),出自 Alec Hogg,“简直太棒了:查理·芒格 1986 年 6 月在哈佛商学院的演讲——‘反转,永远反转’”,BizNews,访问日期:2024 年 2 月 14 日,biznews.com/thought-leaders/1986/06/13/charlie-mungers-speech-to-the-harvard-school-june-1986。

  12. Kurt Lewin, Field Theory in Social Science (New York: Harper and Row, 1951).

    库尔特·勒温,《社会科学中的场论》(纽约:哈珀和罗出版社,1951年)。

  13. Lynn McDonald, “Florence Nightingale, Statistics, and the Crimean War,” Journal of the Royal Statistical Society: Series A 177, no. 3 (June 2014): 569–586.

    Lynn McDonald,“弗洛伦斯·南丁格尔、统计学和克里米亚战争”,皇家统计学会杂志:A 系列 177,第 3 期(2014 年 6 月):569–586。

  14. McDonald, “Florence Nightingale.”

    麦克唐纳,《弗洛伦斯·南丁格尔》。

  15. Edwin W. Kopf, “Florence Nightingale as Statistician,” Publications of the American Statistical Association 15, no. 116 (December 1916): 388–404.

    Edwin W. Kopf,“弗洛伦斯·南丁格尔作为统计学家”,美国统计协会出版物 15,第 116 期(1916 年 12 月):388–404。

  16. Sun Tzu, The Art of War , Lionel Giles, trans. (Los Angeles, Enhanced Media, 2017).

    孙子兵法,莱昂内尔·吉尔斯译(洛杉矶,Enhanced Media,2017)。

Occam’s Razor

奥卡姆剃刀

  1. Charles Mingus, Charles Mingus—More Than a Fake Book (Milwaukee, WI: Hal Leonard Corporation, 1991).

    查尔斯·明格斯,《查尔斯·明格斯——不止是一本假谱集》(威斯康星州密尔沃基:哈尔·伦纳德公司,1991 年)。

  2. James Franklin, The Science of Conjecture: Evidence and Probability before Pascal (Baltimore: Johns Hopkins University Press, 2001).

    James Franklin,《猜想的科学:帕斯卡之前的证据和概率》(巴尔的摩:约翰·霍普金斯大学出版社,2001 年)。

  3. Armand Maurer, “Ockham’s Razor and Chatton’s Anti-Razor,” Mediaeval Studies 46, no. 1 (1984): 463–75.

    Armand Maurer,“奥卡姆剃刀与查顿反剃刀”,中世纪研究 46,第 1 期(1984 年):463-75。

  4. David Hume, An Enquiry Concerning Human Understanding and Other Writings (New York: Cambridge University Press, 2007).

    大卫·休谟,《人类理解研究及其他著作》(纽约:剑桥大学出版社,2007 年)。

  5. Carl Sagan, The Demon-Haunted World: Science as a Candle in the Dark (New York: Random House, 1995).

    卡尔·萨根,《魔鬼出没的世界:科学是黑暗中的一盏明灯》(纽约:兰登书屋,1995 年)。

  6. Sarah Scoles, “How Vera Rubin Confirmed Dark Matter,” Astronomy.com, October 4, 2016, astronomy.com/news/2016/10/vera-rubin .

    Sarah Scoles,“维拉·鲁宾如何证实暗物质”,Astronomy.com,2016 年 10 月 4 日,astronomy.com/news/2016/10/vera-rubin。

  7. Kristine Larsen, “Vera Cooper Rubin,” in Jewish Women: A Comprehensive Historical Encyclopedia , Jewish Women’s Archive, March 1, 2009, jwa.org/encyclopedia/article/rubin-vera-cooper .

    Kristine Larsen,“Vera Cooper Rubin”,载于《犹太妇女:综合历史百科全书》,犹太妇女档案馆,2009 年 3 月 1 日,jwa.org/encyclopedia/article/rubin-vera-cooper。

  8. Richard Panek, “Vera Rubin Didn’t Discover Dark Matter,” Scientific American , December 29, 2016, blogs.scientificamerican.com/guest-blog/vera-rubin-didnt-discover-dark-matter/ .

    Richard Panek,“维拉·鲁宾并没有发现暗物质”,《科学美国人》,2016 年 12 月 29 日,blogs.scientificamerican.com/guest-blog/vera-rubin-didnt-discover-dark-matter/。

  9. Scoles, “How Vera Rubin Confirmed.”

    斯科尔斯,“维拉·鲁宾是如何确认的。”

  10. Lisa Randall, Dark Matter and the Dinosaurs: The Astounding Interconnectedness of the Universe (New York: HarperCollins, 2015).

    Lisa Randall,《暗物质与恐龙:宇宙惊人的相互联系》(纽约:哈珀柯林斯出版社,2015 年)。

  11. Sagan, The Demon-Haunted World .

    萨根,《魔鬼出没的世界》。

  12. Panek, “Vera Rubin Didn’t.”

    帕内克:“维拉·鲁宾没有。”

  13. Francisco Vara-Orta, “A Reservoir Goes Undercover,” Los Angeles Times , June 10, 2008, latimes.com/archives/la-xpm-2008-jun-10-me-balls10-story.html .

    Francisco Vara-Orta,“水库的秘密”,《洛杉矶时报》,2008 年 6 月 10 日,latimes.com/archives/la-xpm-2008-jun-10-me-balls10-story.html。

  14. Marlise Simons, “Face Masks Fool the Bengal Tigers,” New York Times , September 5, 1989, nytimes.com/1989/09/05/science/face-masks-fool-the-bengal-tigers.html .

    Marlise Simons,“口罩骗过了孟加拉虎”,《纽约时报》,1989 年 9 月 5 日,nytimes.com/1989/09/05/science/face-masks-fool-the-bengal-tigers.html。

  15. Louis V. Gerstner Jr., Who Says Elephants Can’t Dance? Leading a Great Enterprise Through Dramatic Change (New York: HarperCollins, 2003).

    Louis V. Gerstner Jr.,《谁说大象不能跳舞?带领伟大的企业经历剧烈的变革》(纽约:HarperCollins,2003 年)。

Hanlon’s Razor

汉隆剃刀

  1. “Thuli Madonsela: SA’s Iron Lady,” Corruption Watch, March 8, 2013, corruptionwatch.org.za/thuli-madonsela-sas-iron-lady/ .

    “图利·马东塞拉:南非的铁娘子”,反腐观察组织,2013 年 3 月 8 日,corruptionwatch.org.za/thuli-madonsela-sas-iron-lady/。

  2. Daniel Kahneman, Thinking, Fast and Slow (New York: Random House, 2011).

    丹尼尔·卡尼曼,《思考,快与慢》(纽约:兰登书屋,2011 年)。

  3. Oscar Wilde, “The Critic as Artist, Part 2,” in Intentions (London: Heinemann and Balestier, 1891).

    奥斯卡·王尔德,《批评家作为艺术家,第二部分》,载于《意图》(伦敦:海涅曼和巴莱斯蒂埃出版社,1891 年)。

  4. Peter Heather, The Fall of the Roman Empire: A New History of Rome and the Barbarians (Oxford, UK: Oxford University Press, 2006).

    Peter Heather,《罗马帝国的衰落:罗马与蛮族的新历史》(英国牛津:牛津大学出版社,2006 年)。

  5. Edward Gibbon, The Decline and Fall of the Roman Empire (New York: Everyman’s Library, 1910).

    爱德华·吉本,《罗马帝国衰亡史》(纽约:Everyman’s Library,1910 年)。

  6. Priscilla Roberts, ed., Cuban Missile Crisis: The Essential Reference Guide (Santa Barbara, CA: ABC-CLIO, 2012).

    Priscilla Roberts 编辑,《古巴导弹危机:基本参考指南》(加利福尼亚州圣巴巴拉:ABC-CLIO,2012 年)。

  7. Robert Heinlein, “Logic of Empire,” Astounding Science Fiction , March 1941.

    罗伯特·海因莱因,《帝国的逻辑》,《惊奇科幻》,1941 年 3 月。

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About the Author

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Shane Parrish is the author of the New York Times bestseller Clear Thinking . He is an entrepreneur and wisdom seeker behind the popular website Farnam Street, where he focuses on turning timeless insights into action. His work has been featured in nearly every major publication, including The New York Times , The Wall Street Journal , and The Economist . His weekly newsletter, Brain Food , has captivated the minds of over half a million subscribers worldwide and his podcast, The Knowledge Project , is one of the most popular in the world.

谢恩·帕里什是《纽约时报》畅销书《清晰思考》的作者。他是一位企业家,也是一位智慧探索者,创办了广受欢迎的网站Farnam Street,致力于将永恒的洞见转化为实际行动。他的作品几乎出现在所有主流媒体上,包括《纽约时报》、《华尔街日报》和《经济学人》。他的每周电子报《脑力食粮》(Brain Food)吸引了全球超过50万订阅者,而他的播客节目《知识项目》(The Knowledge Project)也是世界上最受欢迎的播客之一。

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